ES2933045A1 - AUTOMATED CLASSIFICATION SYSTEM FOR FISH LOINS AND ASSOCIATED PROCEDURE (Machine-translation by Google Translate, not legally binding) - Google Patents
AUTOMATED CLASSIFICATION SYSTEM FOR FISH LOINS AND ASSOCIATED PROCEDURE (Machine-translation by Google Translate, not legally binding) Download PDFInfo
- Publication number
- ES2933045A1 ES2933045A1 ES202130713A ES202130713A ES2933045A1 ES 2933045 A1 ES2933045 A1 ES 2933045A1 ES 202130713 A ES202130713 A ES 202130713A ES 202130713 A ES202130713 A ES 202130713A ES 2933045 A1 ES2933045 A1 ES 2933045A1
- Authority
- ES
- Spain
- Prior art keywords
- fish
- loins
- automated classification
- artificial vision
- camera
- 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
Links
- 238000000034 method Methods 0.000 title claims description 14
- 241000251468 Actinopterygii Species 0.000 claims abstract description 35
- 230000003595 spectral effect Effects 0.000 claims abstract description 11
- 238000000354 decomposition reaction Methods 0.000 claims abstract description 4
- 238000002329 infrared spectrum Methods 0.000 claims abstract description 3
- 230000005055 memory storage Effects 0.000 claims abstract description 3
- 238000003860 storage Methods 0.000 claims abstract description 3
- 230000005855 radiation Effects 0.000 claims abstract 2
- 238000001228 spectrum Methods 0.000 claims description 9
- 238000004458 analytical method Methods 0.000 claims description 6
- 230000004044 response Effects 0.000 claims description 2
- 238000003384 imaging method Methods 0.000 abstract 1
- JVTAAEKCZFNVCJ-UHFFFAOYSA-N lactic acid Chemical compound CC(O)C(O)=O JVTAAEKCZFNVCJ-UHFFFAOYSA-N 0.000 description 24
- 235000014655 lactic acid Nutrition 0.000 description 12
- 239000004310 lactic acid Substances 0.000 description 12
- 235000013372 meat Nutrition 0.000 description 5
- 210000001519 tissue Anatomy 0.000 description 5
- 235000013399 edible fruits Nutrition 0.000 description 3
- 238000004519 manufacturing process Methods 0.000 description 3
- 238000004806 packaging method and process Methods 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 230000007547 defect Effects 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 235000013305 food Nutrition 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 210000003205 muscle Anatomy 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000003307 slaughter Methods 0.000 description 2
- 241001465754 Metazoa Species 0.000 description 1
- 239000012267 brine Substances 0.000 description 1
- 238000009924 canning Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000000295 complement effect Effects 0.000 description 1
- 239000000470 constituent Substances 0.000 description 1
- 238000000151 deposition Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 238000000295 emission spectrum Methods 0.000 description 1
- 238000004186 food analysis Methods 0.000 description 1
- 238000007710 freezing Methods 0.000 description 1
- 230000008014 freezing Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 229910052736 halogen Inorganic materials 0.000 description 1
- 150000002367 halogens Chemical class 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 238000007654 immersion Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 230000037081 physical activity Effects 0.000 description 1
- 238000003908 quality control method Methods 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
- HPALAKNZSZLMCH-UHFFFAOYSA-M sodium;chloride;hydrate Chemical compound O.[Na+].[Cl-] HPALAKNZSZLMCH-UHFFFAOYSA-M 0.000 description 1
- 238000004611 spectroscopical analysis Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000001429 visible spectrum Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light
- G01N21/359—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infrared light using near infrared light
-
- A—HUMAN NECESSITIES
- A22—BUTCHERING; MEAT TREATMENT; PROCESSING POULTRY OR FISH
- A22C—PROCESSING MEAT, POULTRY, OR FISH
- A22C17/00—Other devices for processing meat or bones
- A22C17/0073—Other devices for processing meat or bones using visual recognition, X-rays, ultrasounds, or other contactless means to determine quality or size of portioned meat
-
- A—HUMAN NECESSITIES
- A22—BUTCHERING; MEAT TREATMENT; PROCESSING POULTRY OR FISH
- A22C—PROCESSING MEAT, POULTRY, OR FISH
- A22C25/00—Processing fish ; Curing of fish; Stunning of fish by electric current; Investigating fish by optical means
- A22C25/04—Sorting fish; Separating ice from fish packed in ice
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/02—Food
- G01N33/12—Meat; Fish
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N2021/845—Objects on a conveyor
Landscapes
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Food Science & Technology (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Health & Medical Sciences (AREA)
- Chemical & Material Sciences (AREA)
- General Physics & Mathematics (AREA)
- General Health & Medical Sciences (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Biochemistry (AREA)
- Wood Science & Technology (AREA)
- Zoology (AREA)
- Analytical Chemistry (AREA)
- Medicinal Chemistry (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
Abstract
Description
DESCRIPCIÓNDESCRIPTION
SISTEMA DE CLASIFICACIÓN AUTOMATIZADA DE LOMOS DE PESCADO YAUTOMATED CLASSIFICATION SYSTEM FOR FISH LOINS AND
PROCEDIMIENTO ASOCIADOASSOCIATED PROCEDURE
SECTOR DE LA TÉCNICATECHNIQUE SECTOR
La presente invención se enmarca dentro del sector de la alimentación, más concretamente dentro del campo de los aparatos e instrumentos de medida utilizados en el sector de la alimentación para verificar la calidad de los productos, y más concretamente a los instrumentos de visión artificial que recogen imágenes en diferentes bandas espectrales.The present invention is part of the food sector, more specifically within the field of measuring devices and instruments used in the food sector to verify the quality of products, and more specifically to artificial vision instruments that collect images in different spectral bands.
ANTECEDENTES DE LA INVENCIÓNBACKGROUND OF THE INVENTION
En la actualidad, el proceso de pesca y posterior tratamiento del atún, tiene una relevancia significativa en la calidad de los productos.At present, the fishing process and subsequent treatment of tuna have a significant relevance in the quality of the products.
Como es bien sabido, uno de los problemas más críticos es el denominado Yake, que hace referencia al aspecto quemado que queda en la carne del atún, y que se da si durante el proceso de pesca, los atunes se ven sometidos a un nivel de estrés elevado, de manera que se ven obligados a incrementar la actividad física, produciendo grandes cantidades de ácido láctico en el tejido muscular, que se almacena en el músculo tras el sacrificio del pescado, provocando el precitado cambio de color, textura, e incluso en el sabor de la carne.As is well known, one of the most critical problems is the so-called Yake, which refers to the burned appearance left in the tuna meat, and which occurs if during the fishing process, the tuna are subjected to a level of high stress, so that they are forced to increase physical activity, producing large amounts of lactic acid in muscle tissue, which is stored in the muscle after slaughtering the fish, causing the aforementioned change in color, texture, and even in the taste of meat.
De esta forma, y sobre todo cuando el atún está fresco, la diferencia de aspecto es muy significativa, sin embargo, cuando el atún se congela adquiere un tono pardo muy similar al del tejido afectado por el defecto anterior, haciendo imposible la diferenciación a simple vista, o incluso mediante la utilización de numerosos sistemas de inspección que se basen en el espectro visible.In this way, and especially when the tuna is fresh, the difference in appearance is very significant; however, when the tuna is frozen it acquires a brownish tone very similar to that of the tissue affected by the previous defect, making it impossible to differentiate it with the naked eye. sight, or even through the use of numerous inspection systems that are based on the visible spectrum.
Al desarrollo anterior hay que añadir que el atún se congela desde el primer momento tras el sacrificio del animal, mediante congelación mediante inmersión en salmuera por debajo de los cero grados centígrados. To the previous development it must be added that the tuna is frozen from the first moment after the slaughter of the animal, by freezing by immersion in brine below zero degrees Celsius.
Es decir, nos encontramos ante una situación en la que no es posible realizar una clasificación de la calidad del pescado, diferenciando entre aquella carne afectada por el Yake, y aquella que únicamente está congelada.That is to say, we are faced with a situation in which it is not possible to carry out a classification of the quality of the fish, differentiating between that meat affected by the Yake, and that which is only frozen.
Este problema puede generar que grandes porcentajes de la producción se envíen desde el origen con un gran porcentaje del producto afectado por esta dolencia, de forma que, al ser descongelado para seguir con otra etapa de procesado, como por ejemplo el fileteado, se detecte el problema del yake, de forma que la carne recibida no pueda ser aprovechada para el fin inicial, únicamente para conserva, reduciéndose el valor del producto entre 7 y 10 veces.This problem can cause large percentages of the production to be sent from the origin with a large percentage of the product affected by this ailment, so that when it is thawed to continue with another processing stage, such as filleting, the yake problem, so that the meat received cannot be used for the initial purpose, only for canning, reducing the value of the product between 7 and 10 times.
Es por ello que se hace necesaria la utilización de algún sistema de análisis de la carne del atún, de manera que se pueda detectar la presencia de ácido láctico en el tejido para poder clasificarlo en función del nivel de afectación por yake.That is why it is necessary to use a system for analyzing tuna meat, so that the presence of lactic acid in the tissue can be detected in order to classify it based on the level of yake damage.
En este sentido, existen en el estado de la técnica numerosos documentos que hacen referencia a análisis de alimentos en las líneas de producción, con el objetivo de realizar un control de calidad.In this sense, there are numerous documents in the state of the art that refer to food analysis in production lines, with the aim of carrying out quality control.
Por ejemplo, pertenece al estado de la técnica el documento ES2445245, en el que se describe una celda robotizada con un brazo robotizado, una cinta de alimentación de fruta y varias cintas de salida, que conducen a los distintos tipos de embalaje, con un sistema de iluminación y donde la celda realiza una etapa de procesamiento sobre los frutos, realizando una selección del calibre, una detección de los defectos y un envasado final. Así mismo, comprende también un sistema de visión multiespectral inteligente, que quía al brazo robótico en sus funciones de recogida y depositado de las frutas en sus embalajes, utilizando técnicas de segmentación basadas en visión artificial y técnicas avanzadas de clasificación.For example, document ES2445245 belongs to the state of the art, which describes a robotic cell with a robotic arm, a fruit feeding belt and several output belts, which lead to the different types of packaging, with a system lighting and where the cell performs a stage of processing on the fruit, making a selection of the size, a detection of defects and a final packaging. Likewise, it also includes an intelligent multispectral vision system, which guides the robotic arm in its functions of collecting and depositing the fruit in its packaging, using segmentation techniques based on artificial vision and advanced classification techniques.
Por otro lado, también son ampliamente conocidas las imágenes hiperespectrales que consisten en procesar y recopilar información a lo largo de todo el espectro electromagnético, incluyendo aquellas longitudes de onda que no son visibles para el ojo humano. On the other hand, hyperspectral images are also widely known, which consist of processing and collecting information throughout the entire electromagnetic spectrum, including those wavelengths that are not visible to the human eye.
Mediante estos sistemas, los sensores hiperespectrales apuntan a los objetos utilizando una gran porción del espectro electromagnético, de forma que los diferentes materiales dejan huellas únicas en el todo el espectro utilizado, conocidas como firmas espectrales.Using these systems, hyperspectral sensors target objects using a large portion of the electromagnetic spectrum, so different materials leave unique fingerprints across the entire spectrum used, known as spectral signatures.
Estos sensores han venido siendo utilizados en numerosos sectores, como la agricultura, la minería o la vigilancia, mediante un conjunto de imágenes recopiladas, en la que cada imagen representa un rango del espectro electromagnético, conocido como banda espectral.These sensors have been used in numerous sectors, such as agriculture, mining or surveillance, through a set of collected images, in which each image represents a range of the electromagnetic spectrum, known as a spectral band.
Por ejemplo, podemos encontrar el documento ES2310154, en el que se describe un dispositivo y un método para la obtención de imágenes multiespectrales, a partir de un conjunto de fuentes de luz que son encendidas individualmente y de forma secuencial mediante un sistema de control, mientras una cámara de visión artificial recoge una imagen a cada longitud de onda, a partir de un análisis espectroscópico de los materiales que se quieren diferenciar de la muestra analizada.For example, we can find the document ES2310154, which describes a device and a method for obtaining multispectral images, from a set of light sources that are turned on individually and sequentially by means of a control system, while An artificial vision camera collects an image at each wavelength, based on a spectroscopic analysis of the materials to be differentiated from the analyzed sample.
Sin embargo, ninguno de los sistemas existentes en el mercado y/o pertenecientes al estado de la técnica hace referencia a un método de detección de ácido láctico en piezas de pescado mediante la utilización de imágenes multiespectrales, con el objetivo de determinar la calidad de las mismas a partir de un análisis de los resultados obtenidos.However, none of the existing systems on the market and/or belonging to the state of the art refers to a method for the detection of lactic acid in pieces of fish through the use of multispectral images, with the aim of determining the quality of the images. themselves from an analysis of the results obtained.
EXPLICACIÓN DE LA INVENCIÓNEXPLANATION OF THE INVENTION
El sistema de clasificación automatizada de lomos de pescado que la invención propone se configura, pues, como destacable novedad dentro de su campo de aplicación, ya que a tenor de su implementación y de manera taxativa se alcanzan satisfactoriamente los objetivos señalados, estando los detalles caracterizadores que lo hacen posible y que los distinguen convenientemente recogidos en las reivindicaciones finales que acompañan a la presente descripción.The automated classification system for fish loins that the invention proposes is configured, then, as a remarkable novelty within its field of application, since according to its implementation and exhaustively, the indicated objectives are satisfactorily achieved, the characterizing details being that make it possible and that distinguish them conveniently collected in the final claims that accompany this description.
Concretamente, la invención plantea un método de detección del ácido láctico presente en los lomos de pescado, preferiblemente atún, como sistema que ayude a determinar la calidad de los citados lomos a partir de la cantidad de ácido láctico detectado. Specifically, the invention proposes a method for detecting lactic acid present in fish loins, preferably tuna, as a system that helps determine the quality of said loins based on the amount of lactic acid detected.
Para ello, la presente invención plantea la utilización de imágenes hiperespectrales, mediante las que se analiza la respuesta del tejido del lomo de pescado frente a las diferentes longitudes de onda en la banda de infrarrojo próximo que variarán en función de la cantidad de ácido láctico presente en los lomos. Pudiendo ser utilizado como instrumento de medición para realizar la clasificación.For this, the present invention proposes the use of hyperspectral images, through which the response of the fish loin tissue is analyzed against the different wavelengths in the near infrared band that will vary depending on the amount of lactic acid present. on the loins. It can be used as a measuring instrument to carry out the classification.
Así mismo, se plantea la utilización de una cámara de visión artificial, que obtiene imágenes a partir de sensores espectroscópicos para analizar las líneas de producción, de manera que los lomos de pescado vayan pasando por delante de la cámara, siendo ésta la encargada de recoger las diferentes imágenes línea a línea conforme avanzan los objetos, y realizando la descomposición espectral de cada una de las líneas, produciendo un hipercubo que tendrá tantas bandas como el espectrógrafo y el sensor sean capaces de obtener.Likewise, the use of an artificial vision camera is proposed, which obtains images from spectroscopic sensors to analyze the production lines, so that the fish loins pass in front of the camera, this being the one in charge of collecting the different images line by line as the objects advance, and performing the spectral decomposition of each one of the lines, producing a hypercube that will have as many bands as the spectrograph and the sensor are capable of obtaining.
Por otro lado, se plantea la utilización de iluminación halógena en las zonas en las que se va a realizar el barrido con el escáner, ya que comprende un espectro de emisión plano o relativamente plano en la banda que resulta de interés para el presente cometido. Sin embargo, cabe la posibilidad de que se deba realizar un diseño específico para cada situación, con el objetivo de lograr una uniformidad adecuada al volumen de trabajo y al tamaño del producto.On the other hand, the use of halogen lighting is proposed in the areas where the scan is going to be carried out with the scanner, since it includes a flat or relatively flat emission spectrum in the band that is of interest for the present task. However, it is possible that a specific design must be made for each situation, with the aim of achieving a uniformity appropriate to the volume of work and the size of the product.
Una vez obtenida la anterior información, se procederá a realizar la clasificación de los lomos en función de la cantidad de ácido láctico.Once the above information has been obtained, the loins will be classified according to the amount of lactic acid.
El sistema de clasificación automatizada de lomos de pescado y el conjunto de elementos descritos representan una innovación de características estructurales y constitutivas desconocidas hasta ahora, razones que, unidas a su utilidad práctica, le dotan de fundamento suficiente para obtener el privilegio de exclusividad que se solicita. The automated classification system for fish loins and the set of elements described represent an innovation with hitherto unknown structural and constituent characteristics, reasons that, together with its practical utility, give it sufficient grounds to obtain the requested privilege of exclusivity. .
BREVE DESCRIPCIÓN DE LOS DIBUJOSBRIEF DESCRIPTION OF THE DRAWINGS
Para complementar la descripción que se está realizando y con objeto de ayudar a una mejor comprensión de las características de la invención, se acompaña como parte integrante de dicha descripción, un juego de dibujos en donde con carácter ilustrativo y no limitativo, se ha representado lo siguiente:To complement the description that is being made and in order to help a better understanding of the characteristics of the invention, a set of drawings is attached as an integral part of said description, where, with an illustrative and non-limiting nature, what has been represented has been following:
Figura 1.- Muestra un ejemplo de imagen hiperespectralFigure 1.- Shows an example of a hyperspectral image
Figura 2.- Muestra otro ejemplo de imagen hiperespectralFigure 2.- Shows another example of a hyperspectral image
REALIZACIÓN PREFERENTE DE LA INVENCIÓNPREFERRED EMBODIMENT OF THE INVENTION
En la siguiente descripción detallada de las realizaciones preferentes, se hace referencia a los dibujos adjuntos que forman parte de esta memoria, y en los que se muestran a modo de ilustración realizaciones preferentes específicas en las que la invención puede llevarse a cabo. Estas realizaciones se describen con el suficiente detalle como para permitir que los expertos en la técnica lleven a cabo la invención, y se entiende que pueden utilizarse otras realizaciones y que pueden realizarse cambios lógicos estructurales, mecánicos, eléctricos y/o químicos sin apartarse del alcance de la invención. Para evitar detalles no necesarios para permitir a los expertos en la técnica llevar a cabo la descripción detallada no debe, por tanto, tomarse en un sentido limitativo.In the following detailed description of the preferred embodiments, reference is made to the accompanying drawings which form a part of this specification, and in which are shown by way of illustration specific preferred embodiments in which the invention may be embodied. These embodiments are described in sufficient detail to enable those skilled in the art to carry out the invention, and it is understood that other embodiments may be used and logical structural, mechanical, electrical, and/or chemical changes may be made without departing from the scope. of the invention. To avoid details not necessary to enable those skilled in the art to carry out the detailed description should therefore not be taken in a limiting sense.
Concretamente, la presente invención plantea un sistema de clasificación automatizada de lomos de pescado que comprende al menos una cámara hiperespectral de visión artificial, con al menos una unidad de almacenamiento en memoria y al menos una unidad de control conectada operativamente a los medios anteriores,Specifically, the present invention proposes an automated classification system for fish loins that comprises at least one artificial vision hyperspectral camera, with at least one memory storage unit and at least one control unit operatively connected to the previous means,
Que está caracterizado porque la cámara hiperespectral de visión artificial está configurada para capturar imágenes en una pluralidad de longitudes de onda provenientes de la iluminación de un lomo de pescado del que se quiere obtener una imagen hiperespectral. Which is characterized in that the artificial vision hyperspectral camera is configured to capture images in a plurality of wavelengths coming from the illumination of a fish loin from which a hyperspectral image is to be obtained.
Donde la unidad de control está configurada para realizar una clasificación de los lomos de pescado en función de las imágenes tomadas por la cámara hiperespectral, y en comparación con los datos almacenados en la unidad de almacenamiento.Where the control unit is configured to perform a classification of the fish loins based on the images taken by the hyperspectral camera, and in comparison with the data stored in the storage unit.
Es decir, la presente invención plantea la utilización de un sistema de iluminación y una cámara de visión artificial, que serán capaces de emitir y capturar imágenes en diferentes longitudes de onda, para la obtención de bandas espectrales de los diferentes lomos de pescado.In other words, the present invention proposes the use of a lighting system and an artificial vision camera, which will be capable of emitting and capturing images at different wavelengths, to obtain spectral bands of the different fish loins.
De forma que frente a la banda espectral obtenida, y/o la combinación de las diferentes bandas espectrales, y teniendo en cuenta que aquellas partes que comprendan una mayor cantidad de ácido láctico rebotarán la luz de diferente forma, se podrá detectar la presencia y/o distribución de ácido láctico, así como estimar la cantidad de ácido láctico de cada lomo y, por tanto, la calidad de cada uno de ellos, pudiendo clasificarlos de manera automática.So that compared to the spectral band obtained, and/or the combination of the different spectral bands, and taking into account that those parts that comprise a greater quantity of lactic acid will bounce the light in a different way, it will be possible to detect the presence and/or or distribution of lactic acid, as well as estimating the amount of lactic acid in each loin and, therefore, the quality of each one of them, being able to classify them automatically.
En una realización preferente, la cámara hiperespectral trabajará en la banda de 800 a 1800nm, y pudiendo llegar hasta los 2500nm, es decir, en la parte baja del espectro infrarrojo cercano.In a preferred embodiment, the hyperspectral camera will work in the 800 to 1800nm band, and can reach up to 2500nm, that is, in the lower part of the near infrared spectrum.
Así mismo, en otra realización preferente, los lomos de pescado irán transportados por un elemento de transporte en continuo, como una cinta transportadora, de manera que la cámara hiperespectral está configurada para ir tomando mediciones de todos aquellos lomos de pescado que van circulando por su campo de visión, realizando la clasificación automatizada.Likewise, in another preferred embodiment, the fish loins will be transported by a continuous transport element, such as a conveyor belt, so that the hyperspectral camera is configured to take measurements of all those fish loins that are circulating on its field of view, performing automated classification.
También se presenta el procedimiento de funcionamiento del sistema anterior, que comprenderá al menos los siguientes pasos:The operation procedure of the previous system is also presented, which will include at least the following steps:
- Captura mediante barrido de diferentes imágenes hiperespectrales, donde cada imagen hiperespectral se corresponde con una sección del objeto que se está analizando, en este caso un lomo de pescado;- Scanning capture of different hyperspectral images, where each hyperspectral image corresponds to a section of the object being analyzed, in this case a fish loin;
- A continuación se descompone el espectro de luz en diferentes bandas del espectro para cada sección capturada - The light spectrum is then broken down into different spectrum bands for each section captured
- Se realiza el análisis del lomo de pescado ante la incidencia y la reflexión de las diferentes longitudes de onda;- The analysis of the fish loin is carried out before the incidence and reflection of the different wavelengths;
- Finalmente se realiza la clasificación del lomo de pescado en función del análisis realizado, y en comparación con la información almacenada previamente sobre las proporciones de ácido láctico y los índices de calidad.- Finally, the classification of the fish loin is carried out based on the analysis carried out, and in comparison with the previously stored information on the proportions of lactic acid and the quality indices.
Es decir, se plantea un procedimiento mediante el cual la cámara hiperespectral de visión artificial realiza un barrido de los lomos de pescado, obteniendo la cantidad de ácido láctico presente en cada una de las piezas, permitiendo realizar un análisis y/o una comparación para clasificar y determinar el destino de cada uno de los lomos de pescado.In other words, a procedure is proposed through which the artificial vision hyperspectral camera performs a sweep of the fish loins, obtaining the amount of lactic acid present in each of the pieces, allowing an analysis and/or a comparison to be carried out to classify. and determine the destination of each of the fish loins.
De esta forma, y como se ha comentado con anterioridad, se evita que los lomos de mayor calidad se destinen a los mercados de menor valor y, por el contrario, que aquellos lomos que sean de una calidad inferior se destinen a los mercados que requieren calidades superiores.In this way, and as previously mentioned, higher quality loins are prevented from going to lower value markets and, conversely, lower quality loins from going to markets that require superior qualities.
Particularmente, la clasificación se realizará atendiendo a las diferencias que presenta el tejido sano respecto del tejido afectado con yake a nivel de la luz reflejada a lo largo del espectro mencionado en las descripciones anteriores.Particularly, the classification will be carried out taking into account the differences that healthy tissue presents with respect to tissue affected with yake at the level of reflected light along the spectrum mentioned in the previous descriptions.
Descrita suficientemente la naturaleza de la presente invención, así como la manera de ponerla en práctica, no se considera necesario hacer más extensa su explicación para que cualquier experto en la materia comprenda su alcance y las ventajas que de ella se derivan, haciéndose constar que, dentro de su esencialidad, podrá ser llevada a la práctica en otras formas de realización que difieran en detalle de la indicada a título de ejemplo, y a las cuales alcanzará igualmente la protección que se recaba siempre que no se altere, cambie o modifique su principio fundamental. Having sufficiently described the nature of the present invention, as well as the way of putting it into practice, it is not considered necessary to make its explanation more extensive so that any expert in the field understands its scope and the advantages derived from it, stating that, Within its essentiality, it may be put into practice in other embodiments that differ in detail from the one indicated by way of example, and which will also be covered by the protection that is sought provided that its fundamental principle is not altered, changed, or modified. .
Claims (6)
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| ES202130713A ES2933045A1 (en) | 2021-07-23 | 2021-07-23 | AUTOMATED CLASSIFICATION SYSTEM FOR FISH LOINS AND ASSOCIATED PROCEDURE (Machine-translation by Google Translate, not legally binding) |
| PCT/ES2022/070485 WO2023002087A1 (en) | 2021-07-23 | 2022-07-22 | Automated grading system for fish loins and associated method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| ES202130713A ES2933045A1 (en) | 2021-07-23 | 2021-07-23 | AUTOMATED CLASSIFICATION SYSTEM FOR FISH LOINS AND ASSOCIATED PROCEDURE (Machine-translation by Google Translate, not legally binding) |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| ES2933045A1 true ES2933045A1 (en) | 2023-01-31 |
Family
ID=83115614
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| ES202130713A Pending ES2933045A1 (en) | 2021-07-23 | 2021-07-23 | AUTOMATED CLASSIFICATION SYSTEM FOR FISH LOINS AND ASSOCIATED PROCEDURE (Machine-translation by Google Translate, not legally binding) |
Country Status (2)
| Country | Link |
|---|---|
| ES (1) | ES2933045A1 (en) |
| WO (1) | WO2023002087A1 (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108645798A (en) * | 2018-03-19 | 2018-10-12 | 河南科技学院 | The method of on-line quick detection chicken content of lactic acid bacteria |
| WO2018222048A1 (en) * | 2017-05-29 | 2018-12-06 | Ecotone As | Method and system for underwater hyperspectral imaging of fish |
| US20200193587A1 (en) * | 2018-08-16 | 2020-06-18 | Thai Union Group Public Company Limited | Multi-view imaging system and methods for non-invasive inspection in food processing |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| ES2310154A1 (en) | 2008-05-07 | 2008-12-16 | Universidad De Cantabria. | DEVICE AND METHOD FOR OBTAINING OPTIMIZED MULTIESPECTRAL IMAGES FOR THE DISCRIMINATION OF MATERIALS. |
| WO2010081116A2 (en) * | 2009-01-10 | 2010-07-15 | Goldfinch Solutions, Llc | System and method for analyzing properties of meat using multispectral imaging |
| ES2445245B1 (en) | 2012-08-28 | 2014-12-11 | Universidad De Extremadura | Cell for fruit quality control through an intelligent multispectral vision system and robotic system |
| US9176110B1 (en) * | 2013-09-13 | 2015-11-03 | The United States Of America, As Represented By The Secretary Of Agriculture | Method of determining histamine concentration in fish |
-
2021
- 2021-07-23 ES ES202130713A patent/ES2933045A1/en active Pending
-
2022
- 2022-07-22 WO PCT/ES2022/070485 patent/WO2023002087A1/en not_active Ceased
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2018222048A1 (en) * | 2017-05-29 | 2018-12-06 | Ecotone As | Method and system for underwater hyperspectral imaging of fish |
| CN108645798A (en) * | 2018-03-19 | 2018-10-12 | 河南科技学院 | The method of on-line quick detection chicken content of lactic acid bacteria |
| US20200193587A1 (en) * | 2018-08-16 | 2020-06-18 | Thai Union Group Public Company Limited | Multi-view imaging system and methods for non-invasive inspection in food processing |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2023002087A1 (en) | 2023-01-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| ElMasry et al. | Meat quality evaluation by hyperspectral imaging technique: an overview | |
| CN110057838B (en) | Imaging for determining physical attributes of crustaceans | |
| Sivertsen et al. | Automatic freshness assessment of cod (Gadus morhua) fillets by Vis/Nir spectroscopy | |
| Cheng et al. | Hyperspectral imaging as an effective tool for quality analysis and control of fish and other seafoods: Current research and potential applications | |
| Pu et al. | Recent advances in muscle food safety evaluation: Hyperspectral imaging analyses and applications | |
| Cheng et al. | Non-destructive and rapid determination of TVB-N content for freshness evaluation of grass carp (Ctenopharyngodon idella) by hyperspectral imaging | |
| Zhu et al. | Application of visible and near infrared hyperspectral imaging to differentiate between fresh and frozen–thawed fish fillets | |
| US6587575B1 (en) | Method and system for contaminant detection during food processing | |
| Gowen et al. | Hyperspectral imaging–an emerging process analytical tool for food quality and safety control | |
| He et al. | Nondestructive spectroscopic and imaging techniques for quality evaluation and assessment of fish and fish products | |
| Kamruzzaman et al. | Application of NIR hyperspectral imaging for discrimination of lamb muscles | |
| Kamruzzaman et al. | Non-invasive analytical technology for the detection of contamination, adulteration, and authenticity of meat, poultry, and fish: A review | |
| Xiong et al. | Applications of hyperspectral imaging in chicken meat safety and quality detection and evaluation: a review | |
| Windham et al. | Visible/NIR spectroscopy for characterizing fecal contamination of chicken carcasses | |
| WO2008016309A1 (en) | Multi-modal machine-vision quality inspection of food products | |
| CN102803952A (en) | Hyperspectral identification of egg fertility and gender | |
| Dai et al. | Potential of hyperspectral imaging for non-invasive determination of mechanical properties of prawn (Metapenaeus ensis) | |
| Yang et al. | Prediction of quality traits and grades of intact chicken breast fillets by hyperspectral imaging | |
| Ortega et al. | Perspective chapter: Hyperspectral imaging for the analysis of seafood | |
| ES1305848U (en) | AUTOMATED FISH LONES CLASSIFICATION SYSTEM | |
| Yoon et al. | Embedded bone fragment detection in chicken fillets using transmittance image enhancement and hyperspectral reflectance imaging | |
| ES2933045A1 (en) | AUTOMATED CLASSIFICATION SYSTEM FOR FISH LOINS AND ASSOCIATED PROCEDURE (Machine-translation by Google Translate, not legally binding) | |
| Wu et al. | The use of hyperspectral techniques in evaluating quality and safety of meat and meat products | |
| Kondo | Machine vision based on optical properties of biomaterials for fruit grading system | |
| Charan | A review of hyperspectral imaging in the quality evaluation of meat, fish, poultry and their products. |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| BA2A | Patent application published |
Ref document number: 2933045 Country of ref document: ES Kind code of ref document: A1 Effective date: 20230131 |
|
| PA2A | Conversion into utility model |
Effective date: 20231221 |