Title :
Automated detection of sick pigs based on machine vision
Author :
Zhu, Weixing ; Pu, Xuefeng ; Li, Xincheng ; Zhu, Xiaofang
Author_Institution :
Sch. of Electr. & Inf. Eng., Jiangsu Univ., Zhenjiang, China
Abstract :
An automated detection method for sick pig behavior was proposed after analyzing the disadvantages of traditional observation methods for abnormal behavior of pigs. An embedded detecting system based on computer vision and ARM (Advanced RISC (Reduced Instruction Set Computer) Machines) was designed to monitor the pig excretion behavior. The improved moving objecting detection method and symmetrical pixel block image identification algorithm is designed to recognize the suspected sick pigs. The relevant pictures are taken and sent to the surveillance center through GPRS (General Packet Radio Service) networks after finding the suspected sick pigs. The experiment results for 10 Yorkshire pigs showed that the detection accuracy is about 78.38%. The designed method and monitoring system will be helpful for improving production automation in modern pig farm.
Keywords :
computer vision; farming; image recognition; packet radio networks; Yorkshire pigs; abnormal behavior pigs; automated detection method; embedded detecting system; general packet radio service; image identification algorithm; improving production automation; machine vision; modern pig farm; objecting detection method; pig excretion behavior; reduced instruction set computer; sick pigs based; symmetrical pixel block; traditional observation methods; Algorithm design and analysis; Computer aided instruction; Computer vision; Computerized monitoring; Condition monitoring; Embedded computing; Machine vision; Object recognition; Pixel; Reduced instruction set computing; GPRS; behavior detection; embedded system; machine vision; pig;
Conference_Titel :
Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-4754-1
Electronic_ISBN :
978-1-4244-4738-1
DOI :
10.1109/ICICISYS.2009.5358295
