Pig backfat thickness measuring method and system

A backfat thickness and measuring method technology, applied in the field of pig backfat thickness measuring methods and systems, can solve the problems of difficulty in extracting the backfat area, inaccurate backfat thickness measurement results, and inaccurate extraction results, and achieve accurate measurement. the effect of the result

Pending Publication Date: 2022-01-28
SOUTH CHINA AGRI UNIV
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  • Abstract
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  • Claims
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Problems solved by technology

The image collected by this patent is a color image, which is easily disturbed by light, shadow and its own surface texture, so it is difficult to extract the backfat area, and the extraction result is not accurate enough, and the patent is based on the actual length represented by each pixel Calculate the thickness of backfat, therefore, it will also lead to inaccurate measurement results of backfat thickness

Method used

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  • Pig backfat thickness measuring method and system
  • Pig backfat thickness measuring method and system
  • Pig backfat thickness measuring method and system

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Embodiment 1

[0044] Such as figure 1 As shown, a method for measuring pig backfat thickness in a preferred embodiment of the present invention comprises the following steps:

[0045] S1, collect the RGB-D original video of its walking from the rear of the pig;

[0046] S2. Image segmentation is performed on the key frames in the RGB-D original video to obtain an image of the key region of the pig's buttocks;

[0047] S3. Input the image of the key area of ​​the pig's buttocks into the pre-trained deep learning model in four channels, perform feature extraction, and finally output the predicted fat thickness value.

[0048] This example captures the key area of ​​the back of the pig by collecting RGB-D original video to predict the backfat. Compared with the traditional 2D image technology, the features are more abundant, and the image of the key area of ​​the pig's buttocks is used as four-channel input to the depth Learning the network model keeps the information intact and more reasona...

Embodiment 2

[0071] Such as Image 6 As shown, the present embodiment provides a pig backfat thickness measurement system, comprising:

[0072] The video acquisition module is used to collect the RGB-D original video of the pig walking from the rear. Specifically, the video acquisition module is a 3D camera.

[0073] The key frame determination and pig buttock key area image acquisition module is used to determine the key frame with the pig target from the RGB-D original video, and perform image segmentation on the key frame to obtain the pig buttock key area image. Specifically, the key frame determination and pig buttock key area image acquisition modules use the improved Mask R-CNN model, specifically, the feature extraction network of the Mask R-CNN model uses the lightweight network MobilenetV3. Specifically, the lightweight network MobilenetV3 uses depthwise separable convolution and inverse residual structure, and introduces a lightweight attention module. The key frame determina...

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Abstract

The invention relates to the technical field of animal detection, and discloses a pig backfat thickness measurement method, which comprises the following steps: acquiring an RGB-D video of the hip of a pig, determining a key frame from each frame of image in the RGB-D video by a pre-trained Mask R-CNN model, and obtaining a segmented image with a pig target, wherein a feature extraction network of the Mask R-CNN model adopts a lightweight network MobilenetV3, using a depth separable convolution and inverse residual structure, and introducing a lightweight attention module; according to the physiological part and hip width of the pig, segmenting he segmented image with the pig target to obtain a key region image of the hip of the pig; subjecting the hip key area image of the pig to four-channel input to a trained deep learning model network for fat thickness prediction. The deep learning model network uses a resenet50 backbone network to be combined with an FPN structure, and backfat thickness value prediction is more accurate. In addition, the invention also provides a system for realizing the method.

Description

technical field [0001] The invention relates to the technical field of animal detection, in particular to a method and system for measuring pig backfat thickness. Background technique [0002] The fat thickness of pigs is one of the important indicators reflecting the body condition of pigs. Regulating the feeding amount according to the fat thickness of pigs is an efficient breeding method, which affects the tenderness and flavor of the meat. The traditional and common method of measuring fat thickness is mainly by manual measurement. In the actual production, the breeder strictly follows the general regulations of the international pig industry, and uses the backfat tester to manually measure the backfat of the sow P2 point (the last rib). The measurement result of this method is relatively accurate, but it consumes manpower and material resources, and it is easy to cause the stress response of the pigs, which is not conducive to the welfare of the pigs. [0003] At pre...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/60G06T7/11G01B11/06G06N3/04G06N3/08
CPCG06T7/60G06T7/11G01B11/06G06N3/084G06T2207/10024G06T2207/10016G06T2207/20081G06T2207/20084G06T2207/20016G06N3/045
Inventor 肖德琴刘又夫黄一桂张远琴刘俊彬潘永琪曾瑞麟招胜秋卞智逸
Owner SOUTH CHINA AGRI UNIV
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