An efficient approach for dynamic signature recognition. (2017)

• Record Type: Journal Article
• Authors: El_Rahman, Sahar Abd
• Is Part Of: International journal of intelligent engineering informatics. Volume 5:Number 2(2017)
• Page Start: 167
• Page End: 190
• Publication Date: 2017
• Subjects: biometrics -- dynamic signature identification -- global features -- dynamic time warping -- DTW -- local features -- online signature identification -- online signature recognition; Artificial intelligence -- Engineering applications -- Periodicals; Engineering -- Computer programs -- Periodicals; Knowledge management -- Periodicals; 620.0028563
• Languages: English
• ISSNs: 1758-8715

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%.