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WO2025219789A1 - Authentification de produit à l'aide d'une technologie de registre distribué - Google Patents

Authentification de produit à l'aide d'une technologie de registre distribué

Info

Publication number
WO2025219789A1
WO2025219789A1 PCT/IB2025/053360 IB2025053360W WO2025219789A1 WO 2025219789 A1 WO2025219789 A1 WO 2025219789A1 IB 2025053360 W IB2025053360 W IB 2025053360W WO 2025219789 A1 WO2025219789 A1 WO 2025219789A1
Authority
WO
WIPO (PCT)
Prior art keywords
image
product label
digital representation
block
ledger
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/IB2025/053360
Other languages
English (en)
Inventor
Lindsey L. HINES
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
3M Innovative Properties Co
Original Assignee
3M Innovative Properties Co
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 3M Innovative Properties Co filed Critical 3M Innovative Properties Co
Publication of WO2025219789A1 publication Critical patent/WO2025219789A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/018—Certifying business or products
    • G06Q30/0185—Product, service or business identity fraud
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/50—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols using hash chains, e.g. blockchains or hash trees

Definitions

  • This disclosure relates to using distributed ledger technology in a computing network to implement a stochastic product labeling mechanism.
  • a distributed ledger is a data structure that may be shared and synchronized across a network spanning multiple sites, institutions, and/or geographies. Changes or additions made to the ledger are reflected and copied to many (if not all) computing devices (or nodes) on the network. Often, a distributed ledger is implemented as a consensus network, where nodes on the network implement one or more consensus algorithms intended to achieve reliability or agreement among nodes on the network, even where the network might include multiple unreliable or untrustworthy nodes.
  • Distributed ledgers can be limited in scope to a single entity (e.g., a “private” context ledger), or may bridge different entities (as in the case of “consortium” context ledgers).
  • a blockchain e.g., the technology underlying various cryptocurrencies, such as Ethereum and Bitcoin
  • P2P peer-to-peer
  • Blockchain technology has also permeated the management of other types of computer networks, including local area and wide area networks (LANs and WANs), and is used to support a variety of end-use applications.
  • Each peer (node) on the network maintains a copy of the ledger, and also uses additional measures to help maintain a consensus (which may, in various examples, represent a predetermined quorum) among a number of the nodes on the network.
  • a smart contract is a computer program typically implemented on a consensus network as part of a blockchain or distributed ledger. Smart contracts may be used on a consensus network to facilitate, verify, and/or enforce the negotiation and/or performance of an agreement, contract, or other set of mles.
  • Blockchain a type of distributed digital ledger, is a method rapidly increasing in use to help secure supply chains and fight counterfeit products.
  • Blockchain-based tracking of physical goods still relies on an associated physical code or label to identify items on an individual basis.
  • QR codes, RFID tags, inscribed serial numbers, and other identification mechanisms are widely utilized. While several of these identification methodologies provide advantages in terms of price and readability, they can also be easy to duplicate or tamper with, and can be difficult to incorporate discretely in wearables.
  • a device includes communications circuitry, a memory, and processing circuitry communicatively coupled to the memory.
  • the communications circuitry is configured to receive, via a network, a first image having a first view of a product label included in a wearable item, the first image representing portions of the product label that comprise at least two non-homogeneous materials randomly or pseudorandomly arranged during a production process of the product label.
  • the communications circuitry is further configured to receive, via the network, a second image of the product label.
  • the memory is configured to implement a ledger.
  • the processing circuitry is configured to obtain the first image from the communications circuitry, to generate a first digital representation of the product label based on the arrangement of the at least two non-homogenous materials represented in the first image using a predetermined validation protocol, to store the digital representation to a first block in the ledger implemented in the memory, and to obtain the second image from the communications circuitry.
  • the processing circuitry is further configured to generate a second digital representation of the product label based on the arrangement of the at least two non- homogenous materials represented in the second image, to generate a match probability value based on the first digital representation and the second digital representation, to determine that the first image and the second image are associated with the product label based on the match probability value, and to generate a second block included in the ledger based on the second image, the second block comprising the second image.
  • a method in another example, includes obtaining, by an authentication system, a first image having a first view of a product label included in a wearable item, the first image representing portions of the product label that comprise at least two non-homogeneous materials randomly or pseudorandomly arranged during a production process of the product label. The method further includes generating, by the authentication system, a first digital representation of the product label based on the arrangement of the at least two non-homogenous materials represented in the first image using a predetermined validation protocol.
  • the method further includes storing, by the authentication system, the digital representation to a first block in a ledger, and obtaining, by the authentication system, a second image of the product label, generating, by the authentication system, a second digital representation of the product label based on the arrangement of the at least two non-homogenous materials represented in the second image.
  • the method further includes generating, by the authentication system, a match probability value based on the first digital representation and the second digital representation, and determining, by the authentication system, that the first image and the second image are associated with the product label based on the match probability value.
  • the method further includes generating, by the authentication system, a second block included in the ledger based on the second image, the second block comprising the second image.
  • an authentication apparatus includes means for obtaining a first image having a first view of a product label included in a wearable item, the first image representing portions of the product label that comprise at least two non-homogeneous materials randomly or pseudorandomly arranged during a production process of the product label, means for generating a first digital representation of the product label based on the arrangement of the at least two non-homogenous materials represented in the first image using a predetermined validation protocol, means for storing the digital representation to a first block of a ledger, means for obtaining a second image of the product label, means for generating a second digital representation of the product label based on the arrangement of the at least two non-homogenous materials represented in the second image, means for generating a match probability value based on the first digital representation and the second digital representation, means for determining that the first image and the second image are associated with the product label based on the match probability value, and means for generating a second block included in the ledger based on the second image, the
  • a non-transitory computer-readable storage medium encoded with instructions.
  • the instructions when executed, cause processing circuitry of a computing device to obtain a first image having a first view of a product label included in a wearable item, the first image representing portions of the product label that comprise at least two non-homogeneous materials randomly or pseudorandomly arranged during a production process of the product label, to generate a first digital representation of the product label based on the arrangement of the at least two non-homogenous materials represented in the first image using a predetermined validation protocol, to store the digital representation to a first block of a ledger, to obtain a second image of the product label, to generate a second digital representation of the product label based on the arrangement of the at least two non-homogenous materials represented in the second image, to generate a match probability value based on the first digital representation and the second digital representation, to determine that the first image and the second image are associated with the product label based on the match probability value, and to generate a second block included
  • aspects of this disclosure are directed to systems that use blockchain technology to support tracking and verification in a stochastic product labeling scheme.
  • the systems of this disclosure generate stochastic patterns of retroreflective materials in combination with one or both of non- reflective materials and/or differently reflective materials.
  • the stochastic patterns can then be used to individually mark items, with verification being implemented with a blockchain-backed source of truth.
  • the systems of this disclosure provide one or more technical advantages in the technical fields of digitally driven counterfeit detection and product authentication.
  • the systems of this disclosure provide several technical improvements over existing authentication systems, including several technical improvements over existing authentication systems that combine physical labels even with blockchain-hosted digital data.
  • the systems of this disclosure can leverage existing manufacturing process and would thereby not introduce a cost increase to manufacturers of retroreflective materials.
  • the systems of this disclosure can deliver per-product code variation accomplished without introducing the additional complexities associated with generating specific per-product customizations.
  • the stochastic nature of the product identifiers generated by the systems of this disclosure are difficult to reproduce by counterfeiters, which is a benefit often provided by material-based authentication mechanisms, but in the case of the systems of this disclosure, without the added complexities associated with materialbased authentication mechanisms.
  • Another technical advantage of the system configurations of this disclosure is that downstream manufacturers (e.g., clothing and/or footwear manufacturers) who use the materials (e.g. retroreflective materials supplied by an upstream supplier) are required to implement little or minimal process changes to avail of the stochastic blockchain-hosted authentication techniques of this disclosure. Additionally, the stochastic authentication labels of this disclosure are discrete and easy to incorporate into many different products, and hard to remove from the products. Additionally, the stochastic product authentication labels of this disclosure can be read easily by manufacturers and end user consumers alike with simple image capture devices, such as camera hardware that is commonly integrated into cell phones.
  • Implementations of the subject matter described herein include computer-implemented methods that can be carried out by a system of one or more computers in one or more locations (e.g., via local computing, distributed computing, software as a service (SaaS), etc.) in various examples.
  • SaaS software as a service
  • FIGS. 1A & IB are diagrams illustrating an example implementation of the stochastic product labeling techniques of this disclosure.
  • FIG. 2 is a diagram illustrating the stochastic product label of FIG. IB deployed in a wearable item.
  • FIG. 3 is a block diagram illustrating an example system in which multiple private consensus networks perform decentralized device identification, in accordance with one or more aspects of the present disclosure.
  • FIG. 4 is a flowchart illustrating an example process which authentication systems of this disclosure may perform blockchain-based product label authentication in accordance with one or more aspects of this disclosure.
  • FIG. 5 is a drawing illustrating a laser-processed embodiment of a stochastically modified retroreflective sheet of this disclosure.
  • FIG. 6 is a diagram illustrating the use of flash-enhanced images to implement the blockchainbased product authentication techniques of this disclosure.
  • FIG. 7 is a diagram illustrating two different views of the flash-enhanced image and flash- enhanced segment described with respect to FIG. 6.
  • FIGS. 1 A & IB are diagrams illustrating an example implementation of the stochastic product labeling techniques of this disclosure.
  • FIG. 1A illustrates a retroreflective sheet 2 of this disclosure.
  • Retroreflective sheet 2 includes retroreflective material 4 interspersed with beads 6. While only one instance of beads 6 is called out in FIG. 1 A for ease of illustration purposes, it will be appreciated that retroreflective sheet 2 includes numerous instances of beads 6.
  • Retroreflective material 4 may, in some non-limiting examples, be made of retroreflective microspheres.
  • An example of a retroreflective microsphere-based material is Scotchlite® fabric manufactured and sold by 3M® Company of St. Paul, Minnesota, U.S.A.
  • Beads 6 include one or both of differently reflective beads (e.g., beads having reflectivity properties different from those of retroreflective material 4) and/or non-reflective materials. In various non-limiting examples consistent with aspects of this disclosure, beads 6 may collectively represent a relatively low percentage of the overall surface area of retroreflective sheet 2.
  • Product label generation systems or subsystems of this disclosure may generate the pattern in which beads 6 are dispersed on retroreflective sheet 2 as a random distribution or a pseudorandom distribution.
  • each separate instance of retroreflective sheet 2 may have a different distribution pattern of beads 6.
  • different areas of the same retroreflective sheet 2 may be equipped with different distributions of beads 6.
  • different pieces of retroreflective sheet 2 resulting from the cut may include differing distributions of beads 6.
  • the pattern generation aspects of the systems may dispose a random or pseudorandom percentage and spatial distribution of non-reflective and/or differently reflective beads (in the form of beads 6) onto retroreflective sheet 2 before any portion of retroreflective sheet 2 is applied to or incorporated into a wearable item.
  • the pattern generation aspects of this system may produce visibly different patterns on the surface of retroreflective sheet 2, and thereby enable blockchain-hosted authentication systems of this disclosure to record these visibly different patterns for any defined area that is smaller than the overall area of retroreflective sheet 2.
  • the term “visibly different” may include, but not be limited to, patterns that are discernible as being different to the naked eye, visible to the human eye with eyeglass/contact lens correction, or visible to the human eye with the assistance of various magnification technologies, including digital image enhancements such as upsampling, glass-based magnification, etc.
  • any discrete sub-area of retroreflective sheet 2 has a unique “signature” defined by the random or pseudorandom pattern of a subset of beads 6 that are positioned within the respective discrete sub-area.
  • parties e.g., downstream customers or vertically integrated wearable item manufacturers
  • the pattern generation systems of this disclosure enable the blockchain-hosted authentication systems of this disclosure to uniquely verily the authenticity of each item on an individual basis. That is, the systems of this disclosure may combine to verily the authenticity of each individual item, rather than just items of a single model as a whole.
  • FIG. IB illustrates product label 8 that is defined within retroreflective sheet 2.
  • Product label 8 is one non-limiting example of a discrete sub-area of retroreflective sheet 2 as described above with respect to FIG. 1A.
  • Signature 10 is the unique pattern by which a subset of beads 6 are interspersed with the microspheres of retroreflective material 4 within the discrete sub-area of retroreflective sheet 2 defined by product label 8.
  • the pattern generation systems of this disclosure may enable the generation of multiple unique, stochastic signatures that vary on a per-item basis upon integration of each respective product label on an individual item.
  • the pattern generation systems of this disclosure enables the blockchain-hosted authentication systems of this disclosure to leverage stochastic patterns that are assigned to a digital record on a per-item basis, instead of relying on more resource-heavy and less secure systems such as those that rely on sequential serial numbers or directly encoding specific information into a product label.
  • the stochastic product labels of this disclosure are trackable, and are hosted in a blockchain-based system for added data security based on the verifiability provided by distributed ledger technology.
  • FIG. 2 is a diagram illustrating the stochastic product label 8 deployed in wearable item 12. While FIG. 2 illustrates the example of a shoe, it will be appreciated that product label 8 can be deployed as part of various other types of items, including other wearable items or other types of items for which a party may wish to verify authenticity of source.
  • Product label 8 is extracted from retroreflective sheet 2 shown in FIG. IB, with the unique reflective patterning of signature 10 included within its bounds. In this way, the subset of the stochastic reflective patterning of retroreflective sheet 2 that falls within the bounds of product label 8 equips wearable item 12 with an item-specific unique reflective signature (in the form of signature 10).
  • FIG. 2 illustrates the non-limiting example of smartphone 14 providing the image capture hardware that a party may use to capture an image of product label 8.
  • parties such as downstream purchasers (e.g., retailers and/or end-user customers) may use smartphone 14 to capture an image of product label 8 and upload the digital image to a blockchain-hosted authentication system of this disclosure.
  • the blockchain-hosted authentication system of this disclosure may communicate back to smartphone 14 either a confirmation or a denial with respect to the authentication request, depending on whether the blockchain-hosted authentication system successfully detects a match between signature 10 as shown in the captured image and the ground truth version of signature 10 stored to the blockchain-hosted authentication system as originally captured from retroreflective sheet 2 at the time of production of product label 8.
  • the production of product label 8 may refer to any of a variety of times during the production process, such as a time at which product label 8 is printed on retroreflective sheet 2 and demarcated as a standalone label, or at a time after product label 8 is extracted (e.g., cut) from retroreflective sheet 2.
  • FIG. 3 is a block diagram illustrating an example system in which multiple nodes of a distributed ledger perform product label authentication in accordance with one or more aspects of the present disclosure.
  • System 20 of FIG. 3 includes smartphone 14 shown in FIG. 2 and authentication system 22, both being communicatively connected through network 18.
  • smartphone 14 may send and/or receive product authentication data 16.
  • Smartphone 14 may communicate product authentication data 16 over network 18 to and/or from authentication system 22.
  • authentication system 22 may implement the blockchain-hosted product label authentication techniques of this disclosure in communication with several user-facing devices that are capable of uploading image data over network 18 and receiving authentication confirmations or denials from authentication system 22 over network 18.
  • network 18 may be implemented using any packet-switched network architecture, including aspects of public networks such as the Internet.
  • network 18 may each utilize one or more of a cellular data network, various wired data networks such as those provided by fiber optic infrastructures and/or copper wire infrastructures, Wi-Fi®, ZigBee, Bluetooth®, Near-Field Communication (NFC), satellite, enterprise, service provider, and/or other type of network enabling transfer of transmitting data between computing systems, servers, loT devices, and other computing devices.
  • a cellular data network various wired data networks such as those provided by fiber optic infrastructures and/or copper wire infrastructures, Wi-Fi®, ZigBee, Bluetooth®, Near-Field Communication (NFC), satellite, enterprise, service provider, and/or other type of network enabling transfer of transmitting data between computing systems, servers, loT devices, and other computing devices.
  • network 18 may incorporate a wired network and/or wireless network, such as a local area network (LAN), a wide area network (WAN), a Wi-FiTM based network or 5G network, an Ethernet® network, a mesh network, a short-range wireless (e.g., Bluetooth®) communication medium, and/or various other computer interconnectivity infrastructures and standards.
  • Network 18 may support various levels of network access, such as to public networks (e.g., the Internet), to private networks (e.g., as may be implemented by educational institutions, enterprises, governmental agencies, etc.), or private networks implemented using the infrastructure of a public network (e.g., a virtual private network or “VPN” that is tunneled over the Internet).
  • public networks e.g., the Internet
  • private networks e.g., as may be implemented by educational institutions, enterprises, governmental agencies, etc.
  • VPN virtual private network
  • a variety of client devices, server devices, or other devices may transmit and receive data, commands, control signals, and/or other information across the networks illustrated in FIG. 3 using any suitable communication techniques.
  • the number of devices supported by network 18 is highly scalable.
  • the infrastructure of network 18 may include communication hardware of various communication ranges and wireless/wire-based capabilities, such as one or more network hubs, network switches, network routers (wired and/or wireless), satellite dishes, set-top boxes, Ethernet® cards, WiFi® receivers, RFID readers/transmitters, or any other network equipment.
  • Such devices or components may be operatively inter-coupled, thereby providing for the exchange of information between computers, devices, or other components.
  • FIG. 3 may be operatively coupled to the networks shown in FIG. 3 using one or more network links.
  • the links coupling such devices or systems may be Ethernet or other types of network connections, and such connections may be wireless and/or wired connections.
  • One or more of the devices or systems illustrated in FIG. 3 or otherwise on network 18 may be in a remote location relative to one or more other illustrated devices or systems.
  • authentication system 22 includes power source 42, processing circuitry 38, one or more communication circuitry units 34, one or more input devices 40, one or more output devices 36, and one or more storage devices 30.
  • Storage devices 30 may store one or more blockchains 26, ledger data store 38, and rules 32.
  • One or more of the devices, modules, storage areas, or other components of authentication system 22 are interconnected to enable inter-component communications (physically, communicatively, and/or operatively).
  • such connectivity may be provided by communication channels 44, which may include one or more of a system bus, a network connection, an inter-process communication data structure, or any other hardware capable of communicating data.
  • Power source 42 of authentication system 22 may provide power to one or more components of authentication system 22.
  • Power source 42 may receive power from the primary alternating current (AC) power supply in a building, data center, server farm, home, or other location.
  • power source 42 may be a battery or a device that supplies direct current (DC).
  • authentication system 22 and/or power source 42 may receive power from another source.
  • One or more of the devices or components illustrated within authentication system 22 may be connected directly or indirectly to power source 42, and/or may receive power directly or indirectly from power source 42.
  • Power source 42 may have intelligent power management or consumption capabilities, and such features may be controlled, accessed, or adjusted by one or more components of authentication system 22 and/or by processing circuitry 38 to intelligently consume, allocate, supply, conserve, or otherwise manage power.
  • Processing circuitry 38 of authentication system 22 may implement functionality and/or execute instructions associated with authentication system 22 or associated with one or more modules illustrated herein and/or described below.
  • Processing circuitry 38 may be, may be part of, and/or may include programmable processing circuitry and/or fixed-function circuitry that performs operations in accordance with one or more aspects of the present disclosure.
  • Example implementations of processing circuitry 38 may include, be, or be part of one or more microprocessors, application processors, display controllers, auxiliary processors, graphics processors, central processing units, one or more sensor hubs, and any other hardware configured to function as a processing device.
  • Authentication system 22 may invoke processing circuitry 38 to perform operations in accordance with one or more aspects of the present disclosure using hardware, firmware, software, or a mixture of hardware, software, and firmware residing in and/or executing at authentication system 22.
  • Communication circuitry unit 34 may enable authentication system 22 to communicate with devices external to authentication system 22 by transmitting and/or receiving data, and may operate, in some respects, as both an input interface and an output interface. In some examples, communication circuitry unit 34 may enable authentication system 22 to communicate with other devices over network 18. In other examples, communication circuitry unit 34 may send and/or receive radio signals on a radio network such as a cellular radio network. In other examples, communication circuitry unit 34 of authentication system 22 may transmit and/or receive satellite signals on a satellite network such as a Global Positioning System (GPS) network.
  • GPS Global Positioning System
  • Non-limiting examples of hardware that communication circuitry unit 34 may be, be part of, or include are network interface cards (such as Ethernet® cards or WiFi® cards), an optical transceiver, a radio frequency transceiver, a GPS receiver, an RFID transmitter or reader, or any other type of device that can send and/or receive information.
  • Other examples of communication circuitry unit 34 may include devices capable of communicating over Bluetooth®, GPS, NFC, ZigBee, and cellular networks (e.g., 3G, 4G, 5G), and Wi-Fi® radios found in mobile devices as well as Universal Serial Bus (USB) controllers and the like. Such communications may adhere to, implement, or abide by appropriate protocols, including Transmission Control ProtocoFIntemet Protocol (TCP/IP), Ethernet, Bluetooth®, NFC, or other technologies or protocols.
  • TCP/IP Transmission Control ProtocoFIntemet Protocol
  • Ethernet Bluetooth®
  • NFC or other technologies or protocols.
  • Input devices 40 may represent any input devices of authentication system 22 not otherwise separately described herein.
  • One or more input devices 40 may generate, receive, and/or process input from any type of device capable of detecting input from a human or machine.
  • one or more input devices 40 may generate, receive, and/or process input in the form of electrical, physical, audio, image, and/or visual input (e.g., peripheral device, keyboard, microphone, camera).
  • Output devices 36 may represent any output devices of authentication system 22 not otherwise separately described herein.
  • One or more output devices 36 may generate, receive, and/or process input from any type of device capable of detecting input from a human or machine.
  • one or more output devices 36 may generate, receive, and/or process output in the form of electrical and/or physical output (e.g., peripheral device, actuator, etc.).
  • Storage devices 30 may store information for processing during operation of authentication system 22.
  • storage devices 30 may include internal storage positioned within authentication system 22, or may represent external storage, such as removable storage or external hard drives or solid-state drives (SSDs), or may incorporate both internal and external storage components.
  • Storage devices 30 may store program instructions and/or data associated with one or more of the units/modules described in accordance with one or more aspects of this disclosure.
  • Processing circuitry 38 and one or more storage devices 30 collectively provide an operating environment or platform for the units/modules described herein, which may be implemented as software, but may in some examples include any combination of hardware, firmware, and software.
  • Processing circuitry 38 may execute instructions and one or more storage devices 30 may store instructions and/or data of one or more modules.
  • the combination of processing circuitry 38 and storage devices 30 may, in concert, retrieve, store, and/or execute the instructions and/or data of one or more applications, modules, or software.
  • Processing circuitry 38 and/or storage devices 30 may also be operably /communicatively coupled to one or more other components, including, but not limited to, one or more of the components of authentication system 22 and/or one or more devices or systems (e.g., smartphone 14) illustrated as being connected to authentication system 22.
  • one or more storage devices 30 are temporary memories, meaning that a primary purpose of these particular one or more of storage devices 30 is not long-term storage.
  • Storage devices 30 of authentication system 22 may be configured for short-term storage of information as volatile memory and therefore not retain stored contents if deactivated. Examples of volatile memories include random access memories (RAM), dynamic random access memories (DRAM), static random access memories (SRAM), and other forms of volatile memories known in the art.
  • RAM random access memories
  • DRAM dynamic random access memories
  • SRAM static random access memories
  • Storage devices 30 in some examples, also include one or more computer-readable storage media. Storage devices 30 may be configured to store larger amounts of information than volatile memory. Storage devices 30 may further be configured for long-term storage of information as non-volatile memory space and retain information after activate/off cycles.
  • non-volatile memories examples include magnetic (or “spinning”) hard drives, optical discs, solid state drives (SSDs), flash memories, or forms of electrically programmable memories (EPROM) or electrically erasable and programmable (EEPROM) memories.
  • Blockchains 26 may store verified images of product label 8 with signature 10. It will be appreciated that authentication system 22 may use blockchains 26 to store verified images of numerous product labels and unique signatures. However, purely for ease of discussion, this disclosure describes these functionalities of authentication system 22 and blockchains 26 with respect to the non-limiting example of product label 8 and signature 10. For instance, the original manufacturer of retroreflective sheet 2 may upload a ground truth image of product label 8 with signature 10 included in it over network 18 to authentication system 22.
  • Authentication system 22 may invoke communication circuitry unit 34 to receive the verified image and may invoke blockchains 26 to store the verified image to storage devices 30, such as to a block (referred to herein as a “first block”) of ledger 28.
  • first block a block of ledger 28.
  • first is not used to herein to designate any particular position within ledger data store 28, but rather, to distinguish this particular block from other blocks of ledger data store 28 that will be used to store other data, as will be described further at other parts of this disclosure.
  • processing circuitry 38 may invoke blockchains 26 to generate a digital representation of a portion of wearable item 12 (e.g., a portion that includes the entirety of product label 8 with the entirety of signature 10 within its borders) based on the verified image received over network 18, and to store the generated digital representation of this portion of wearable item 12 to the first block of ledger data store 28.
  • a portion of wearable item 12 e.g., a portion that includes the entirety of product label 8 with the entirety of signature 10 within its borders
  • Processing circuitry 38 may apply one or more of validation protocols 32 as part of invoking blockchains 26 to generate the digital representation of the portion of wearable item 10 that is then stored to the block of ledger data store 28. For instance, processing circuitry 38 may apply one or more of validation protocols 32 to determine that the received image form which the digital representation is generated is a verified image. That is, in this particular example, processing circuity 38 may apply the respective one or more validation protocols 32 to confirm that the generated digital representation corresponds to a ground truth image of product label 8 with signature 10 included, and to thereby establish that the digital representation stored at the first block of ledger data store 28 can be used to verify later-received images purporting to represent wearable item 12.
  • An attribute (and a potentially unique attribute) of the digital representation stored to the first block of ledger data store 28 is the arrangement of two or more non-homogenous materials as represented in the verified image.
  • the arrangement of the two or more non-homogeneous materials in the verified image maps to a two- dimensional rendering of the patterning of beads 6 throughout retroreflective material 4 within product label 8 (i.e. the patterning of signature 10).
  • processing circuitry 38 may generate the digital representation of the received image based on the arrangement of the non-homogenous materials as shown in the image.
  • authentication system 22 may invoke communication circuitry 34 to obtain a second image.
  • communication circuitry 34 may receive the second image from smartphone 14.
  • the second image may represent a portion of a wearable item with a product label that includes a signature made up of an arrangement of at least two non-homogenous materials.
  • a user may use smartphone 14 to capture the second image of the product label.
  • One example of the image that the user may use smartphone 14 to capture is an image product label 8 with signature 10 included, after product label 8 has been deployed by way of integration into wearable item 12.
  • Examples of users who may use smartphone 14 may be a downstream wholesaler, a retailer that sells wearable item 12 to an end customer, or the end customer who purchases or considers purchasing wearable item 12.
  • Processing circuitry 38 may generate a second digital representation based on the second image.
  • the second image may also represent a product label as shown in the second image with an arrangement of two or more non-homogenous materials.
  • Processing circuitry 38 may generate the second digital representation based on the arrangement of the two or more non-homogenous materials represented in the second image.
  • processing circuitry 38 may compare the first digital representation that is stored to the first block of ledger data store 28 against the second digital representation generated from the second image received from smartphone 14.
  • processing circuitry 38 may generate a match probability with respect to the first digital representation (that is stored to the first block of ledger data store 28) and the second digital representation that is generated from the second image received from smartphone 14. Based on the match probability, processing circuitry 38 may determine whether or not the product label shown in the second image is authentic. For instance, if the match probability meets or exceeds a predetermined threshold value, then processing circuitry 38 may determine that the arrangement of the non- homogenous materials as shown in the second image received from smartphone 14 matches (within a predetermined acceptable margin of error), the arrangement of beads 6 among retroreflective material 4 as shown in the original verification image of product label 8 containing signature 10.
  • processing circuitry 38 of authentication system 22 may determine that the second image received from smartphone 14 represents an authentic instance of wearable item 12. If processing circuitry 38 determines that the second image represents an authentic instance of wearable item 12, processing circuitry 38 may invoke blockchains 26 to generate a second block in ledger data store 28, and store the second digital representation (generated from the second image) to the second block of ledger data store 28.
  • the term “second” is not used herein to designate any particular position within ledger data store 28, but rather, to distinguish this particular block from other blocks of ledger data store 28 that will be used to store other data, as will be described further at other parts of this disclosure. For instance, the second block is different from the “first block” of ledger data store 28, which stores the digital representation of the verified ground truth image of product label 8.
  • the two or more non-homogenous materials include multiple microspheres.
  • retroreflective material 4 may be made up of retroreflective microspheres, and beads 6 may include microspheres.
  • beads 6 may include non-reflective microspheres and/or microspheres that have reflective properties that differ from those of the retroreflective microspheres of retroreflective material 4.
  • the microsphere(s) of retroreflective material 4 have a first reflectivity value and the microsphere(s) of beads 6 include at least one microsphere with a second reflectivity value that is different from the first reflectivity value.
  • retroreflective material 4 may be made up of glass microspheres.
  • beads 6 may include glass microspheres and/or non-glass microspheres.
  • Retroreflective material 4 forms a first portion retroreflective sheet 2 with a first reflectivity value
  • beads 6 (or a subset thereof) form a second portion of retroreflective sheet 2 with a second reflectivity value that is different from the first reflectivity value.
  • the first reflectivity value may be lower than the second reflectivity value.
  • the second reflectivity value may be lower than the first reflectivity value (e.g., with the second reflectivity value corresponding non-reflectivity in a subset of these examples).
  • processing circuitry 38 may detect the pattern in which beads 6 (or the subset thereof that are included in signature 10) are arranged within the boundary of product label 8, and may generate the first digital representation (to be stored to the first block of ledger data store 28) based on the detected pattern.
  • processing circuitry 38 may determine a boundary portion included in the product label based on the first image (e.g., as defined by the closed boundary of product label 8 in FIGS. IB and 2), where the boundary portion demarcates the portions of product label 8 that include the at least two non-homogeneous materials defined by the portions of retroreflective material 4 and beads 6 that make up signature 10.
  • processing circuitry 38 may determine a plurality of location values based on portions of a first material included in the at least two non-homogeneous materials, the portions of the first material being substantially enclosed within the boundary portion (e.g., the portions of retroreflective material 4 that are enclosed within the closed boundary defined by the outer rim of product label 8).
  • the boundary of product label 8 is not included in the at least two non- homogenous materials, in that the boundary may be made of a material different from both of retroreflective material 4 and also different from the material that makes up at least one subset of beads 6.
  • each location value included in the plurality of location values is associated with a substantially similarly sized portion of one of the non-homogenous materials. For instance, two or more of beads 6 may be substantially similarly sized.
  • the two or more substantially similarly sized beads of beads 6 may be microspheres.
  • two or more of the retroreflective microspheres of retroreflective material 4 may be substantially similarly sized.
  • the substantially similarly sized microspheres may include glass microspheres.
  • ledger data store 28 represents a private distributed ledger.
  • FIG. 4 is a flowchart illustrating an example process 50 by which authentication system 22 may perform blockchain-based product label authentication in accordance with one or more aspects of this disclosure.
  • Process 50 may begin with authentication system 22 obtaining an image of product label 8 (52).
  • image of product label 8 For instance, communication circuitry 34 of authentication system 22 may receive an image that the original manufacturer of retroreflective sheet 2 uploads over network 18.
  • the obtained image may represent all of retroreflective sheet 2, or may include a sub-portion of retroreflective sheet 2 that includes the entirety of product label 8 with signature 10 included.
  • Processing circuitry 38 of authentication system 22 may verily the image as a ground truth image of product label 8 (54). For instance, processing circuitry 38 may apply one or more of validation protocols 32 to generate a digital representation based on the received image and confirm that the digital representation does indeed represent a ground truth image of product label 8 and signature 10. In some examples processing circuitry 38 may generate the digital representation at least in part by implementing one or more pre-processing and/or post-processing operations on the obtained image.
  • processing circuitry 38 may store the generated digital representation of the ground truth image to a first block of ledger data store 28 (56).
  • first is not necessarily used herein to designate any particular position of the block within ledger data store 28, but instead, to distinguish this particular block from other blocks of ledger data store 28 that will be used to store other data, as described further at other parts of this disclosure.
  • authentication system 22 may leverage the added data security and verifiability provided by blockchain technology when using the ground truth image to process authentication requests with respect to product label 8 after product label 8 is deployed.
  • Communication circuitry 34 of authentication system 22 may receive an authentication request over network 18 (58). For instance, a user may use smartphone 14 to capture a second image of product label 8 (with signature 10 included) as deployed via its inclusion in wearable item 12. In response to a user request, smartphone 14 may generate an authentication request that includes the second image, and upload the authentication request (with the second image included) via network 18 to authentication system 22.
  • Processing circuitry 38 of authentication system 22 may apply one or more of validation protocols 32 to compare the second image received in the authentication request to the ground truth image stored to the first block of ledger data store 28. Based on the comparison operations conducted in accordance with the one or more applied validation protocols 32, processing circuitry 38 generate a match probability between the first image that is verified as the ground truth image and the second image received in the authentication request (60).
  • the match probability generated by processing circuitry 38 according to the one or more of validation protocols 32 may represent a probability value that the second image included in the authentication request is a true picture of product label 8 with signature 10 included.
  • processing circuitry 38 may apply the one or more of validation protocols 32 to generate the match probability based on how closely the representation of the patterning of the at least two non-homogenous materials in the second image matches the patterning of signature 10 as represented by the verified ground truth image stored to the first block of ledge data store 28.
  • processing circuitry 38 may apply the one or more of validation protocols to implement one or more image comparison algorithms such as keypoint extraction & matching (e.g., as provided by the SIFT keypoints algorithm), a sum of absolute differences (SAD) algorithm, a structural similarity index measure (SSIM) based algorithm, a histogram-based algorithm, decision trees (or a combination of decision trees with keypoint extraction & matching), discrete cosine transformation (DCT) based algorithms, block-based analyses, pixelbased checks (including, but not limited to, pixel-by -pixel scanning using various ordering mechanisms, such as raster scans), etc.
  • image comparison algorithms such as keypoint extraction & matching (e.g., as provided by the SIFT keypoints algorithm), a sum of absolute differences (SAD) algorithm, a structural similarity index measure (SSIM) based algorithm, a histogram-based algorithm, decision trees (or a combination of decision trees with keypoint extraction & matching), discrete cosine transformation (DCT) based algorithms, block-
  • processing circuitry 38 may determine whether or not the match probability meets a threshold value (decision block 62).
  • the match probability generated by processing circuitry 38 may represent a value between two predetermined bounds, namely, a lower bound and an upper bound.
  • the threshold value may be a value between the aforementioned bounds and predetermined by authentication system 22 or another system.
  • processing circuitry 38 may detect a threshold satisfying-event if the match probability is equal to or greater than the threshold value, and may detect a threshold meet-failure if the match probability is less than the threshold value.
  • processing circuitry 38 may deny the authentication request received over network 18 (68). In some examples of the authentication request being denied, processing circuitry 38 may invoke communication circuitry 34 to communicate a denial communication over network 18 to smartphone 14. In this scenario, authentication system 22 implements the blockchain- hosted verification techniques of this disclosure to inform a user of smartphone 14 of a possible counterfeit product or other type of non-authenticity associated with wearable item 12.
  • processing circuitry 38 may store the second image received in the authentication request (or a digital representation generated therefrom) to a second block of ledger data store 28 (64).
  • second is not used herein to designate any particular position within ledger data store 28, but rather, to distinguish this particular block from other blocks of ledger data store 28 that will be used to store other data, as will be described further at other parts of this disclosure.
  • the second block is different from the “first block” of ledger data store 28, which stores the digital representation of the verified ground truth image of product label 8.
  • processing circuitry 38 may approve the authentication request received over network 18 (66). In some examples of the authentication request being approved, processing circuitry 38 may invoke communication circuitry 34 to communicate an approval communication over network 18 to smartphone 14. In this scenario, authentication system 22 implements the blockchain- hosted verification techniques of this disclosure to provide the user of smartphone 14 a confirmation of the authenticity of the source identifier associated with wearable item 12 (namely, by way of verifying the authenticity of signature 10 within product label 8).
  • process 50 is illustrated according to one example sequence in FIG. 4, it will be appreciated that, in accordance with various aspects of this disclosure, the operations may be performed in various other sequences, with some operations being performed partially or fully in parallel.
  • authentication system 22 may perform operations 64 and 66 in a different order, or partially or entirely concurrently.
  • FIG. 5 is a drawing illustrating a laser-processed embodiment of a stochastically modified retroreflective sheet of this disclosure. While retroreflective sheet 2 and its associated stochastic patterning have been described above with respect to a bead-based implementation, it will be appreciated that the stochastic patterning may be implemented in the designs and prints of this disclosure by way of other techniques as well.
  • sheet region 70 includes a portion of a random or pseudorandom pattern implemented on a first material (namely, retroreflective material 4) using a second material that has different reflective properties from the first material because of a laser-based processing of certain areas of retroreflective material 4.
  • the embodiment shown in FIG. 5 includes a second material that is obtained by laser-processing certain areas of retroreflective material 4 within sheet region 70.
  • the example of sheet region 70 (which is a portion of the overall retroreflective sheet 2) includes four separate laser- processed zones that have reflective properties that differ from the reflective properties of retroreflective material 4.
  • pattern generation systems of this disclosure may generate a random or pseudorandom scattering pattern for laser-processed areas of sheet region 70.
  • a robotic controller or pointing apparatus may move or reorient a laser (a specialized light emission device) according to the scattering pattern and activate the laser at the specific points of the movement/orientation pattern at which the scattering pattern includes laser-processed areas.
  • Sheet region 70 of FIG. 5 represents a subarea of retroreflective sheet 2 shown in FIG. 1.
  • sheet region includes four separate areas at which retroreflective material 4 is laser- processed. More specifically, the example of FIG. 5 shows sheet region 70 as including four laser- processed area. The four laser-processed areas are shown in FIG. 5 by way of feature 72A, feature 72B, feature 72C, and feature 72D (collectively, “features 72”). Additionally, in some examples (such as in the example of sheet region 70), the pattern generation systems of this disclosure may vary the size of the second material by varying the laser spot times for different laser-processed areas.
  • FIG. 5 illustrates laser-processed area sizes produced by decreasing laser spot times, from left to right along the horizontal axis of sheet region 70.
  • feature 72A has a diameter of 263.3 microns
  • feature 72B has a diameter of 200.1 microns
  • feature 72C has a diameter of 213.7 microns
  • feature 72D has a diameter of 154.3 microns.
  • the unit of measurement “microns” is also referred to as a “micrometre” or “micrometer” and is denoted by the symbol “pm.”
  • the systems of this disclosure leverage the effect of laser processing to alter the reflective properties of retroreflective material 4.
  • features 72 specific areas of retroreflective material 4
  • the systems of this disclosure generate two different materials on the surface of sheet region 70, namely, the unprocessed areas of retroreflective material 4 and the post-laser-processed areas represented by features 72.
  • the laser processing of features 72 causes the first and second materials (namely, retroreflective material 4 and features 72) to have different reflective properties from one another.
  • retroreflective material 4 is retroreflective while features 72 are non-reflective.
  • retroreflective material 4 is retroreflective while features 72 are reflective, with different light-reflective property parameters from retroreflective material 4.
  • two or more of features 72 may have different reflective properties from one another (e.g., due to different laser wavelengths and/or spot times being applied to retroreflective material 4), thereby causing sheet region 70 to have greater than two materials in terms of reflective properties.
  • Features 72 (which are laser-processed portions of retroreflective material 4) and beads 6 are two examples of a second material that the systems of this disclosure may use to dispose a differently reflective (second) material among the retroreflective (first) material formed by the microspheres of retroreflective material 4.
  • systems of this disclosure may form the second (differently reflective) material disposed across the first material (retroreflective material 4) in other ways.
  • the systems of this disclosure may randomly or pseudorandomly crush one or more microspheres of retroreflective material 4, thereby altering the reflective properties of these crushed microspheres.
  • the systems of this disclosure may feed the random or pseudorandom pattern to a robotic controller that controls the movement of one or more spools to operate the spool(s) in a way that the random/pseudorandom pattern is represented in the selective crushing operations implemented by the robotic controller using the spool(s).
  • the systems of this disclosure may randomly or pseudorandomly “score” or “scratch” areas of retroreflective material 4, thereby altering the reflective properties of the scored areas of retroreflective material 4.
  • FIG. 6 is a diagram illustrating the use of flash-enhanced images to implement the blockchainbased product authentication techniques of this disclosure.
  • FIG. 6 shows non-flash-enhanced image 74A and flash-enhanced image 74B (collectively, “authentication images 74”).
  • Each of authentication images 74 may be captured using any user-controlled image capture hardware, including camera- integrated computing devices such as smartphone 14.
  • Each of authentication images 74 may represent some or all of signature 10, or an area that encompasses signature 10.
  • FIG. 6 illustrates the image clarity that is added by leveraging nearly ubiquitously available flashbulb capabilities in terms of providing authentication information to authentication system 22.
  • the pattern included in signature 10 is more easily interpretable by image-processing aspects of authentication system 22 in flash-enhanced image 74B.
  • the improved interpretability of flash-enhanced image 74B provides the technical improvement of data precision in terms of the pattern-matching functionalities used to implement the blockchain-hosted product authentication techniques of this disclosure.
  • the systems of this disclosure leverage flash-enhancement of captured images to improve consistency across different images used for authentication. For instance, flash-enhancement may correct for lighting differences between the environments in which the ground truth image is captured and in which one or more authentication images are captured. Moreover, the systems of this disclosure may leverage flash-enhancement to provide consistent authentication decision results (e.g. the results of executing decision block 62 of FIG. 4) across multiple authentication images, thereby providing consistent results while mitigating or potentially even eliminating false-positives and/or false-negatives with respect to the authentication decision.
  • FIG. 6 illustrates flash-enhanced segment 76.
  • Flash-enhanced segment 76 represents a portion of flash-enhanced image 74B, and illustrates the level of detail or granularity provided by flash-enhanced image 74B with respect to image analysis functionalities, such as those implemented by aspects of authentication system 22.
  • the level of detail and granularity and detail provided by flash-enhanced segment 76 is applicable to various embodiments of signature 10.
  • Such embodiments of signature 10 include examples of signature 10 being formed using bead inlay or overlay (as described with respect to the use of beads 6), in examples of signature 10 being formed using laser processing (as described with respect to the use of laser-processed features 72), in examples of signature 10 being formed using random or pseudorandom patterns of crushing microspheres of retroreflective material 4, in examples of signature 10 being formed by scoring retroreflective material 4, etc.
  • flash-enhanced image 74A forming a part of a ground truth image that authentication system 22 verifies using one or more of validation protocols 32 and stores to the first block of ledger data store 28, the level of granularity shown in flash-enhanced segment 76 provides the technical improvement of an accurate ground truth image against which authentication system 22 can compare later-received authentication images.
  • the level of granularity shown in flash-enhanced segment 76 enables aspects of authentication system 22 to perform authentication operations (such as authentication request approval 66 or authentication request denial 68 shown in FIG. 4) using an accurate authentication image.
  • systems of this disclosure leverage flash-enhanced images, which are almost ubiquitously available because of flashbulb technology being integrated into numerous easily available image capture devices, to provide the technical improvement of enhanced data precision with respect to the image processing used to authenticate product labels and product source identification.
  • FIG. 7 is a diagram illustrating two different views of the flash-enhanced image and flash- enhanced segment described with respect to FIG. 6.
  • FIG. 7 illustrates flash-enhanced image 74B and flash-enhanced segment 76 of FIG. 6.
  • Flash-enhanced image 74B represents an image taken with smartphone 14 with the flash functionality activated, and from a distance of approximately one foot away from product label 8.
  • the patterning shown in flash-enhanced image 74 and flash-enhanced segment 76 include features of approximately 200 microns in diameter or distance across the longest axis.
  • the diameters (or generally “sizes”) of the features may all fall within the 154.3 micron to 263.3 micron range shown in FIG. 5, or some other range in which the lower and upper bounds are within a relatively small maximum deviation from the value of 200 microns.
  • FIG. 7 also illustrates flash-enhanced pan image 78, which includes flash-enhanced pan segment 82.
  • Flash-enhanced pan image 78 represents the same area shown in flash-enhanced image 74B, but captured from a farther distance. While flash-enhanced image 74B represents a view of a portion of signature 10 from approximately one foot away, flash-enhanced pan image 78 represents a view of the same portion of signature 10 from approximately three feet away.
  • flash- enhanced segment 76 represents a view of a sub-portion of signature 10 from approximately one foot away, flash-enhanced pan segment 82 represents a view of the same sub-portion of signature 10 from approximately three feet away.
  • the non-homogenous texturing of product label 8 is visible from approximately one foot away, but is not visible to the human eye (even via un-zoomed digital image capture) from a distance of even three feet away.
  • the product label generation systems of this disclosure maintain aesthetic quality of items, such as product label 8 in particular and of wearable item 12 at large, while enabling stochastic, block-chain hosted product authentication functionalities that provide improved image analysis reliability and reduced or potentially eliminated false-positives and/or false-negatives.
  • processors including one or more microprocessors, CPUs, GPUs, DSPs, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), processing circuitry (e.g., fixed function circuitry, programmable circuitry, or any combination of fixed function circuitry and programmable circuitry), or any other equivalent integrated or discrete logic circuitry, as well as any combinations of such components.
  • processors including one or more microprocessors, CPUs, GPUs, DSPs, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), processing circuitry (e.g., fixed function circuitry, programmable circuitry, or any combination of fixed function circuitry and programmable circuitry), or any other equivalent integrated or discrete logic circuitry, as well as any combinations of such components.
  • a control unit comprising hardware may also perform one or more of the techniques of this disclosure.
  • Such hardware, software, and firmware may be implemented within the same device or within separate devices to support the various operations and functions described in this disclosure.
  • any of the described units, modules or components may be implemented together or separately as discrete but interoperable logic devices. Depiction of different features as modules or units is intended to highlight different functional aspects and does not necessarily imply that such modules or units must be realized by separate hardware or software components. Rather, functionality associated with one or more modules or units may be performed by separate hardware or software components or integrated within common or separate hardware or software components.
  • Computer readable medium such as a computer-readable storage medium, containing instmctions. Instructions embedded or encoded in a computer-readable storage medium may cause a programmable processor, or other processor, to perform the method, e.g., when the instmctions are executed.
  • Computer readable storage media may include random access memory (RAM), read only memory (ROM), programmable read only memory (PROM), erasable programmable read only memory (EPROM), electronically erasable programmable read only memory (EEPROM), flash memory, a hard disk, a CD-ROM, a floppy disk, a cassette, magnetic media, optical media, or other computer readable media.

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Abstract

Un procédé comprend l'obtention d'une première image ayant une première vue d'une étiquette de produit présente dans un article pouvant être porté et représentant des parties de l'étiquette de produit qui comprennent au moins deux matériaux agencés de manière aléatoire ou pseudo-aléatoire, la génération d'une première représentation numérique de l'étiquette de produit sur la base de l'agencement des matériaux représentés dans la première image à l'aide d'un protocole de validation, le stockage de la représentation numérique sur un premier bloc dans un registre, l'obtention d'une seconde image de l'étiquette de produit, la génération d'une seconde représentation numérique de l'étiquette de produit sur la base de l'agencement des matériaux représentés dans la seconde image, la génération d'une valeur de probabilité de correspondance sur la base de la première et de la seconde représentation numérique, la détermination que la première et la seconde image sont associées à l'étiquette de produit sur la base de la valeur de probabilité de correspondance, et la génération d'un second bloc inclus dans le registre pour stocker la seconde image.
PCT/IB2025/053360 2024-04-15 2025-03-31 Authentification de produit à l'aide d'une technologie de registre distribué Pending WO2025219789A1 (fr)

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20100327050A1 (en) * 2006-03-13 2010-12-30 Smi Holdings, Inc. Expression codes for microparticle marks based on signature strings
WO2020028288A1 (fr) * 2018-07-31 2020-02-06 Avery Dennison Corporation Systèmes et procédés pour empêcher la contrefaçon
US20200410188A1 (en) * 2019-03-29 2020-12-31 At&T Intellectual Property I, L.P. Apparatus and method for identifying and authenticating an object

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20100327050A1 (en) * 2006-03-13 2010-12-30 Smi Holdings, Inc. Expression codes for microparticle marks based on signature strings
WO2020028288A1 (fr) * 2018-07-31 2020-02-06 Avery Dennison Corporation Systèmes et procédés pour empêcher la contrefaçon
US20200410188A1 (en) * 2019-03-29 2020-12-31 At&T Intellectual Property I, L.P. Apparatus and method for identifying and authenticating an object

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