Edge Detection Based on Robust Least Squares Support Vector Machines with Multiple Kernel

Based on the powerful nonlinear mapping ability of kernel learning,a novel method for edge extraction was proposed to overcome the over-fitting of original LS-SVM and improve the robustness of original LS-SVM.Particle Swarm Optimization(PSO) algorithm was used to the optimize the parameters.Compared with Canny method,BP neural network and standard LS-SVM,it is shown that the proposed method is effective and has better performance than other algorithms under the same condition,it is a very practical image processing algorithm.