Peng et al., 2025 - Google Patents
Single-snapshot multi-frequency demodulation in spatial frequency domain imaging enables real-time, accurate and wide-field optical property measurement of fruitsPeng et al., 2025
- Document ID
- 11811261626296366374
- Author
- Peng Y
- Jia T
- Chen X
- Hu C
- Zhou G
- Hu D
- Publication year
- Publication venue
- Food Control
External Links
Snippet
Spatial frequency domain imaging (SFDI) enables nondestructive, depth-resolved detection and is particularly well-suited for visualizing subsurface defects in fruits. However, traditional SFDI methods require multiple acquisitions to gather information at different frequencies and …
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20048—Transform domain processing
- G06T2207/20056—Discrete and fast Fourier transform, [DFT, FFT]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
-
- 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 infra-red, visible or ultra-violet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
-
- 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 infra-red, visible or ultra-violet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/47—Scattering, i.e. diffuse reflection
- G01N21/4795—Scattering, i.e. diffuse reflection spatially resolved investigating of object in scattering medium
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
- G06T5/007—Dynamic range modification
- G06T5/008—Local, e.g. shadow enhancement
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Sun et al. | Detection of early decay in peaches by structured-illumination reflectance imaging | |
| Li et al. | Apple quality identification and classification by image processing based on convolutional neural networks | |
| Jia et al. | Essential processing methods of hyperspectral images of agricultural and food products | |
| Gao et al. | Application of hyperspectral imaging technology to discriminate different geographical origins of Jatropha curcas L. seeds | |
| Barman et al. | Smartphone image based digital chlorophyll meter to estimate the value of citrus leaves chlorophyll using Linear Regression, LMBP-ANN and SCGBP-ANN | |
| Mendoza et al. | Integrated spectral and image analysis of hyperspectral scattering data for prediction of apple fruit firmness and soluble solids content | |
| CN103822879B (en) | A kind of Fructus actinidiae chinensis based on high light spectrum image-forming technology expand fruit lossless detection method | |
| Li et al. | Vessel segmentation and width estimation in retinal images using multiscale production of matched filter responses | |
| Zhang et al. | Detection and classification of potato defects using multispectral imaging system based on single shot method | |
| Chen et al. | Soft X-ray image recognition and classification of maize seed cracks based on image enhancement and optimized YOLOv8 model | |
| Thakur et al. | Deep transfer learning based photonics sensor for assessment of seed-quality | |
| US10215642B2 (en) | System and method for polarimetric wavelet fractal detection and imaging | |
| CN117607960A (en) | Leakage source positioning method and device, computer equipment and storage medium | |
| CN113935906B (en) | Strong reflection stripe noise removing method for Fourier domain optical coherence tomography | |
| Yang et al. | Early apple bruise recognition based on near-infrared imaging and grayscale gradient images | |
| Li et al. | Detection of bruising in pear with varying bruising degrees and formation times by using SIRI technique combining with texture feature-based LS-SVM and ResNet-18-based CNN model | |
| Chatterjee et al. | An efficient automated biospeckle indexing strategy using morphological and geo-statistical descriptors | |
| Zhang et al. | Development of a hyperspectral imaging system for the early detection of apple rottenness caused by P enicillium | |
| Zhang et al. | Detection of bruised apples using structured light stripe combination image and stem/calyx feature enhancement strategy coupled with deep learning models | |
| Li et al. | Enhanced detection of early bruises in apples using near-infrared hyperspectral imaging with geometrical influence correction for universal size adaptation | |
| Peng et al. | Single-snapshot multi-frequency demodulation in spatial frequency domain imaging enables real-time, accurate and wide-field optical property measurement of fruits | |
| Li et al. | “Two-dimensional Terraced Compression method “and its application in contour detection of transmission image | |
| Jin-li et al. | Detection the internal quality of watermelon seeds based on terahertz imaging combined with image compressed sensing and improved-real-ESRGAN | |
| JP2013509630A (en) | Apparatus and method for adjusting a raised pattern of a hyperspectral image. | |
| Leopold et al. | Use of Gabor filters and deep networks in the segmentation of retinal vessel morphology |