DocumentCode :
2070999
Title :
An Automatic Dead Chicken Detection Algorithm Based on SVM in Modern Chicken Farm
Author :
Zhu, Weixing ; Peng, Yansong ; Bin Ji
Author_Institution :
Sch. of Electr. & Inf. Eng., Jiangsu Univ., Zhenjiang, China
fYear :
2009
fDate :
26-28 Dec. 2009
Firstpage :
323
Lastpage :
326
Abstract :
An automatic detection algorithm for dead birds based on support vector machine (SVM) is proposed. Firstly, according to the changes of central region of cockscomb in the picture, logic and operation is used to remove the image of live chickens; Secondly, in order to distinguish accurately the dead birds in processed picture, the perimeter, area, eccentricity and complexity of the cockscomb are extracted as the variables. The changes of these variables are defined as the feature vectors. The samples of the above feature vectors are used to train SVM classifier. During the training, the grid search method is used to optimize the kernel width and punishment factor of SVM and the classifier for dead bird is designed finally. The results of experiment show that the detection accuracy is over 90%.
Keywords :
farming; feature extraction; image classification; learning (artificial intelligence); search problems; support vector machines; SVM classifier training; automatic dead chicken detection algorithm; cockscomb complexity; dead birds; eccentricity; feature vectors; grid search method; live chickens; modern chicken farm; picture processing; punishment factor; support vector machine; training; Birds; Data mining; Design optimization; Detection algorithms; Information science; Logic; Pattern recognition; Search methods; Support vector machine classification; Support vector machines; automatic detection; dead chicken detection; modern chicken farm; support vector machine (SVM);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Engineering (ISISE), 2009 Second International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-6325-1
Electronic_ISBN :
978-1-4244-6326-8
Type :
conf
DOI :
10.1109/ISISE.2009.62
Filename :
5447214
Link To Document :
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