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Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/869

Title: Improved Offline Signature Verification Scheme using Feature Point Extraction Method
Authors: Jena, D
Majhi, B
Panigrahy, S K
Jena, S K
Keywords: computational geometry
feature extraction
fraud
handwriting recognition
pattern classification
statistical analysis
Issue Date: 2008
Publisher: IEEE
Citation: 7th IEEE International Conference on Cognitive Informatics, ICCI, Stanford, August 14-16, 2008.
Abstract: In this paper a novel offline signature verification scheme has been proposed. The scheme is based on selecting 60 feature points from the geometric centre of the signature and compares them with the already trained feature points. The classification of the feature points utilizes statistical parameters like mean and variance. The suggested scheme discriminates between two types of originals and forged signatures. The method takes care of skill, simple and random forgeries. The objective of the work is to reduce the two vital parameters False Acceptance Rate (FAR) and False Rejection Rate (FRR) normally used in any signature verification scheme. In the end comparative analysis has been made with standard existing schemes.
URI: http://10.1109/COGINF.2008.4639204
http://hdl.handle.net/2080/869
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