Offline Signature Identification by Fusion of Multiple Classifiers using Statistical Learning Theory

Details Offline Signature Identification by Fusion of Multiple Classifiers using Statistical Learning Theory Offline Signature Identification by Fusion of Multiple Classifiers using Statistical Learning Theory

2010-03-30

arxiv.org/abs/1003.5865v1

Computer Science

Computer Vision and Pattern Recognition

11 pages, 3 figures, IJSIA 2010

Scientific paper

This paper uses Support Vector Machines (SVM) to fuse multiple classifiers for an offline signature system. From the signature images, global and local features are extracted and the signatures are verified with the help of Gaussian empirical rule, Euclidean and Mahalanobis distance based classifiers. SVM is used to fuse matching scores of these matchers. Finally, recognition of query signatures is done by comparing it with all signatures of the database. The proposed system is tested on a signature database contains 5400 offline signatures of 600 individuals and the results are found to be promising.

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