New two-stage method of fingerprint classification

A new two-stage method of fingerprint classification is proposed that is based on hidden Markov model (HMM) and support vector machine (SVM). This technique uses FingerCode as the representation of the fingerprint. After classifiers are trained, five pseudo 2-D HMM classifiers are used to firstly select the most possible two classification results. Furthermore, the corresponding SVM classifier is selected to make the final decision. In the end, this new approach is tested by 2000 images selected from the NIST-4 database and 1000 images from the CQU-VERID-ICOM database. A classification accuracy of 91 percent and a classification consistency of 93.7 percent are achieved. The results demonstrate the effectiveness of this approach.