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Live pig walking stride frequency extraction method based on depth image skeleton end analysis

A technology of skeleton endpoints and depth images, applied in image analysis, image data processing, instruments, etc.

Inactive Publication Date: 2014-06-25
JIANGSU UNIV
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Problems solved by technology

[0004] The purpose of the present invention is to overcome the shortcomings of relying on manual observation or intrusive detection devices in the existing method for extracting the stride frequency of live pigs, and provide a long-distance, non-invasive automatic extraction method for the stride frequency of pigs based on computer vision

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  • Live pig walking stride frequency extraction method based on depth image skeleton end analysis
  • Live pig walking stride frequency extraction method based on depth image skeleton end analysis
  • Live pig walking stride frequency extraction method based on depth image skeleton end analysis

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Embodiment Construction

[0022] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments. The processing flow of the embodiment of the present invention is as follows figure 1 shown. Using the depth camera Kinect as the image acquisition device, the moving image sequence of the pig is collected sideways. Lateral acquisition refers to the angle between the movement direction of the pig and the horizontal plane of the optical axis of the depth camera at about 90°. In the pig house environment, the spatial distribution of walls and facilities around the pig house is different from that of the target pigs, making the foreground of the pigs more obvious in the depth image. By using the background subtraction preprocessing method to filter out the environmental background such as side walls, beams and columns, a better foreground image sequence of live pigs can be obtained, such as figure 2 shown.

[0023] Further, ea...

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Abstract

The invention discloses a live pig walking stride frequency extraction method based on depth image skeleton end analysis. The extraction method includes the steps of removing backgrounds in depth camera images, extracting skeletons, pruning the skeletons and matching skeleton drawings, the ends of the pectoral appendage skeleton and the pelvic appendage skeleton of a live pig in all frames of images are extracted, the far side attribute and the near side attribute of the ends of the two skeletons are judged, a sine curve is fitted through change point sets of coordinate relations of the far sides and the near sides of the fore limbs and the posterior limbs of the live pig in the image frames of a live pig motion sequence, and then the live pig walking stride frequency characteristics are extracted. The extraction method has the advantages of long distance, non-invasion and automatic extraction based on computer vision; the feature extraction process is simple and easy to implement; the extraction method not only is suitable for collecting the live pig walking stride frequency features, but also can be used for detecting walking stride frequency of a horse, a bull, a sheep and other animals walking with the four limbs.

Description

technical field [0001] The invention relates to a biological image processing technology, in particular to the extraction of hog movement step frequency characteristics applied to the monitoring of abnormal behavior of hogs in large-scale hog breeding. Background technique [0002] my country is a big country in pork consumption and pig breeding. In recent years, with the progress of my country's urbanization construction and environmental protection, the pig breeding model has rapidly evolved from scattered farming by farmers in the past to factory-scale farming. However, explosive outbreaks often cause serious losses to breeding enterprises. Building a computer vision pig disease monitoring and early warning system can help breeding enterprises detect early disease symptoms of pigs as soon as possible, and take measures such as isolation, disinfection, and treatment in time to avoid outbreaks. [0003] As a typical biological characteristic, gait characteristics have attr...

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Application Information

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IPC IPC(8): G06T7/00G06T7/20
Inventor 朱伟兴刘波李新城
Owner JIANGSU UNIV
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