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Research And Implementation Of Sheep’s Body Size Parameters Measurement System Based On Binocular Stereo Vision

Posted on:2020-08-28Degree:MasterType:Thesis
Country:ChinaCandidate:Y H ShenFull Text:PDF
GTID:2393330578956460Subject:Agriculture
Abstract/Summary:PDF Full Text Request
In recent years,with the rapid development of animal husbandry,sheep industry,which occupies an important position in animal husbandry,has also shown a rapid development trend.The size parameters of sheep are important indicators reflecting the quality of sheep breeds,production performance,growth and development,health status and fruitfulness.At present,most of the measurement of sheep’s body size is based on manual contact measurement.This traditional measurement method needs not only the experience of the surveyor,but also the low accuracy,large workload,long measurement time and easy to cause stress response in sheep.In order to solve the problems arising from traditional measurement and realize the non-contact and non-stress measurement of sheep body size,a non-contact measurement system of sheep body size is needed.In this paper,a method of acquiring sheep body size parameters based on binocular vision is proposed.Binocular cameras are used to capture side images of model sheep,and the powerful graphical user interface(GUI)of Matlab is used to develop a measuring system of sheep body size based on binocular vision.The functions of camera calibration,sheep contour extraction,point identification,manual matching,three-dimensional coordinate recovery and body size calculation are realized.Three-dimensional coordinate recovery and sheep body size calculation functions.Experiments show that the system can effectively measure the body size of sheep,and the relative error of the measured body size is less than 2.5%.The binocular vision measurement system studied and designed in this paper can be used to measure the body size of sheep without stress,which provides a new method for developing welfare breeding of sheep.The main work of this paper is as follows:(1)Calibration of Binocular Vision Measurement System.Firstly,the basic coordinate system and its conversion relationship and the camera imaging model are mastered;then the pixel coordinates of the circular feature points are calculated;finally,combined with Zhang’s calibration method,and the inside and outside parameters of the camera are obtained.(2)Contour extraction.Firstly,the goat image is segmented by threshold,and the goat body and background are separated.Then the binary image is processed morphologically to remove holes and small links.Finally,the goat contour is extracted.(3)Measurement point recognition.Firstly,the inflection points on the sheep contour are detected,and then the sheep body measurement points are identified on the basis of the inflection points,and the coordinates of the measurement points are extracted for reserve.(4)Body size calculation.For the coordinate labeling of left and right sheep images,the same serial number means that the manual matching is successful.Using the internal and external parameters obtained by camera calibration,the three-dimensional coordinates of the matched measuring points are restored,and finally the calculation of sheep size parameters is completed.(5)The realization of binocular vision measurement system.Firstly,the GUI interface is designed for camera calibration module,Contour extraction module,measuring point recognition module and body size calculation module,and then the functions of each module are realized.The interface of each module of the experimental system is built by GUI provided by matlab.The interface is clear,concise and easy to operate.This paper provides theoretical basis and experimental support for the realization of non-contact measurement of sheep body size.Therefore,binocular vision measurement system can be a new way to replace manual contact measurement.
Keywords/Search Tags:Sheep body size parameter, Binocular vision, Camera calibration, Contour extraction, Measurement point recognition, Body size calculation
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