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Multi-Layer Framed Offline Signature Recognition Algorithm

W. U. Wickramaarachchi and S. Vasanthapriyan
Department of Computing & Information Systems, Sabaragamuwa University of Sri Lanaka, Belihuloya, Sri Lanka

Abstract—This research experiment ventures to find a solution for automating the framed signature recognition. Here signatures are made on a given frame using a ballpoint pen with a tip size of 0.5. Instead of direct neural networks based algorithm implementation, the extracted non-scale variant and scale variant features are used in a support vector machine in signature recognition algorithm. The outcome of the research appears as a GUI. The final outcome was 100% random signature isolation with over 88% trained forgery rejection. If not for 4 vulnerable signatures, this rate goes over 96% however the research carried out with worst environmental conditions and with least number of features. Thus, the results can be definitely improvable with modifications.

Index Terms—image preprocessing, feature extraction, signature recognition, offline

Cite: W. U. Wickramaarachchi and S. Vasanthapriyan, "Multi-Layer Framed Offline Signature Recognition Algorithm," Journal of Image and Graphics, Vol. 3, No. 1, pp. 11-15, June 2015. doi: 10.18178/joig.3.1.11-15