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 |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
improved.pdf | 687.17 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.