High speed real-time foreign recognition based on hypersphere one-class support vector machines
Fuguang Yao, Xianxin Zhong · 2009
Aim at the foreign randomicity and the color difference between the regular materiel and the foreign in high speed real-time foreign recognition, an approach to real-time foreign recognition based on hypersphere one-class support vector machines is presented. In this method, regular materiel are considered as training samples, and OC-SVM is used to obtain the color distributing of the regular materiel, that is to find out the foreign whose color are not in the range of the regular materiel. To train and simplify OC-SVM, centrifugal coefficient π is presented, and Zoutendijk fastest decline method is adopted to search for working set. The result of experiment shows, this method has good performance in foreign recognition, especially for some foreign whose color is similar to that of regular materiel. Contrast to Gaussian distribution fitting method, the general accuracy of recognition is 8~10% higher.