A Hybrid HMM/ANN Based Approach for Online Signature Verification
Zhong-Hua Quan, De-Shuang Huang, Kunhong Liu, Kwok‐wing Chau · IEEE International Conference on Neural Networks/IEEE ... International Conference on Neural Networks · 2007
This paper presents a new approach based on HMM/ANN hybrid for online signature verification. A group of ANNs are used as local probability estimators for an HMM. The Viterbi algorithm is employed to work out the global posterior probability of a model. The proposed HMM/ANN hybrid has a strong discriminant ability, i.e, from a local sense, the ANN can be regarded as an efficient classifier, and from a global sense, the posterior probability is consistent with that of a Bayes classifier. Finally, the experimental results show that this approach is promising and competing.