An Automatic Dead Chicken Detection Algorithm Based on SVM in Modern Chicken Farm
Weixing Zhu, Yansong Peng, Bin Ji · 2009
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%.