Improved Hybrid HMM-SVM Method for Handwritten Chinese Signature Verification
An improved hybrid HMM-SVM method for Handwritten Chinese Signature Verification is proposed.First HMM is used as discriminative feature transformation and data compression for two kinds of training data of signature.Then the multidimensional probability output vectors of HMM are treated as the input vectors for SVM.At last in order to improve the performance of verification,the output vectors of SVM are transformed to a posterior probability through sigmoid function.Some experiments with this method are made on the SVC2004 Signature database.The result indicates that the proposed method can get better performance such as lower EER compared to HMM,SVM and HMM-SVM.