Frozen fresh pomfret freshness rapid grading method based on deep learning

A grading method and deep learning technology, applied in image analysis, image data processing, instruments, etc., can solve problems such as physical and chemical changes in microorganisms, life and health threats, inedible fish, etc., to protect health and interests, expand data volume, and promote The effect of sustainable and healthy development

Pending Publication Date: 2020-10-13
CHINA AGRI UNIV
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  • Abstract
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Problems solved by technology

But its water content is high, the muscle fiber is short, the muscle tissue is fragile, and it is easy to grow and reproduce bacteria; and its endogenous enzymes are rich; Zhao Yongqiang, Li Na, etc. published in "Journal of Dalian Ocean University, 2016, 31(04): 456 -462." "Research Progress on Fish Freshness Evaluation Indexes and Determination Methods" points out that if combined with improper handling and storage, physical and chemical changes and spoilage caused by microorganisms will easily occur, and spoiled fish meat not only It is inedible and poses a threat to human life and health

Method used

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  • Frozen fresh pomfret freshness rapid grading method based on deep learning
  • Frozen fresh pomfret freshness rapid grading method based on deep learning
  • Frozen fresh pomfret freshness rapid grading method based on deep learning

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Embodiment

[0065] (1) In order to improve the operating efficiency of the system without affecting the prediction performance, the original image size is scaled from 5184 pixels × 3456 pixels × 3 pixels to 1024 pixels × 1024 pixels by the method of INTER_AREA (local pixel resampling). 640 pixels x 3 pixels.

[0066] (2) Label all scaled images using Labelme software and divide them into four freshness grades: first-level freshness, second-level freshness, spoilage, and corruption. The effects of pictures with different freshness levels are as follows Image 6 shown:

[0067] (3) For the eyes of the pomfret, the corresponding labels are eye1, eye2, eye3, and eye4; for the gills of the pomfret, the corresponding labels are gill1, gill2, gill3, and gill4. After labeling, each image will generate a corresponding json file. The labeling effect is as Figure 7 In a, the picture before labeling; the picture after labeling in b is shown.

[0068] (4) Using the method of data enhancement, X-...

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Abstract

The invention discloses a frozen fresh pomfret freshness rapid grading method based on deep learning, which belongs to the technical field of refrigerated food quality evaluation. Specifically, freshness grading is carried out on a pomfret image based on a Mask R-CNN technology, a frozen fresh pomfret image is obtained, a digital image data set is established, feature learning is fused into the process of establishing the model, accurate detection and segmentation are carried out on fisheye and gill parts, feature learning can be carried out autonomously, and the freshness of the pomfret can be accurately segmented and classified. Therefore, quick detection and intelligent prediction of the quality deterioration of the frozen fresh pomfret are realized; and the expandability and mobility of the model are improved. A rapid, low-cost, accurate, nondestructive and real-time automatic detection technology is realized, and the health and benefits of consumers are guaranteed. Product qualityis controlled for different varieties of cold chain storage and transportation environments and supply chain sources, and technical support is provided for public health and epidemic prevention.

Description

technical field [0001] The invention belongs to the technical field of refrigerated food quality assessment, and in particular relates to a deep learning-based rapid freshness classification method for chilled pomfret, in particular to a Mask R-CNN-based semantic segmentation method to achieve freshness classification for pomfret images, The model implements end-to-end training, can be embedded on mobile terminals, and integrates a portable rapid assessment system for chilled pomfret freshness for producers and consumers. Background technique [0002] Fish is rich in protein, minerals and vitamins, with low fat content and good taste. It is an important part of people's diet structure. However, its water content is high, muscle fibers are short, muscle tissue is fragile, and it is easy for bacteria to grow and reproduce; and its endogenous enzymes are rich; Zhao Yongqiang, Li Na, etc. published in ". Dalian Ocean University Journal, 2016, 31(04): 456 -462." on "Fish freshne...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/11G06T7/187
CPCG06T7/0004G06T2207/20081G06T2207/20084G06T2207/30128G06T7/11G06T7/187
Inventor 李振波杨晋琪余晓杨泳波李晔岳峻
Owner CHINA AGRI UNIV
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