An efficient approach for dynamic signature recognition Online publication date: Tue, 16-May-2017
by Sahar Abd El_Rahman
International Journal of Intelligent Engineering Informatics (IJIEI), Vol. 5, No. 2, 2017
Abstract: Online signature recognition is an accepted biometric technique, because it is less expensive than other biometric techniques. In this paper, an efficient two-stage online signature recognition approach is presented. This approach depends on the initial analyses of global features using Euclidean distance to quickly discard outlier signatures; then followed by local features analysis using an enhanced DTW algorithm. An emphasis was created to extract stroke-associated features for global recognition phase as well as for signal pre-processing prior to local recognition. Stroke-related features used in the proposed system contribute well in enhancing the run-time performance by quick discriminating genuine and forgery signatures. Experiments are run out on MCYT-100 benchmark database. The proposed system is tested with 100 users - including 25 skilled forgery signatures and 25 genuine signatures per each user. The worst FAR recorded value is less than 4%, FRR is less than 20% and EER is less than 5%.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Intelligent Engineering Informatics (IJIEI):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook