By Topic

A New Decision Making Approach for Improving the Performance of Automatic Signature Verification Using Multi-sets of Features

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Ammar, M. ; Biomed. Eng. Dept., Damascus Univ., Damascus, Syria ; Watanabe, T. ; Fukumura, Teruo

So far, Automatic Signature Verification (ASV) approaches using a threshold-based decision have depended on one feature set for distance measure and a threshold on this distance measure for verification. The best performance that can be reached in this case is the one obtained by using the best feature set (bfs). In this paper, we introduce a new decision making approach for ASV that uses Multi-Sets of Features (MSF). The MSF provides higher performance than that obtainable by using the bfs, with better forgery detection. The improvement is seen to be significant because it recovers some lost effectiveness and can add it to that of the bfs. This gain in effectiveness is highly desirable when we deal with signatures of high value documents.

Published in:

Frontiers in Handwriting Recognition (ICFHR), 2010 International Conference on

Date of Conference:

16-18 Nov. 2010