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On-line Signature Verification Based on GA-SVM
2015
International Journal of Online Engineering (iJOE)
With the development of pen-based mobile device, on-line signature verification is gradually becoming a kind of important biometrics verification. This thesis proposes a method of verification of on-line handwritten signatures using both Support Vector Data Description (SVM) and Genetic Algorithm (GA). A 27-parameter feature set including shape and dynamic features is extracted from the on-line signatures data. The genuine signatures of each subject are treated as target data to train the SVM
doi:10.3991/ijoe.v11i6.5122
fatcat:uajj2jquffdvlkjx2u6nobnghe