Hindi and English Off-line Signature Identification and Verification

Abstract

Biometric systems play a significant role in the field of information security as they are extremely required for user authentication. Signature identification and verification have a great importance for authentication intention. The purpose of this paper is to present an empirical contribution towards the understanding of multi-script (Hindi and English) signature verification. This system will identify whether a claimed signature belongs to the group of English signatures or Hindi signatures from a combined Hindi and English signature datasets and then it will verify signatures using these two resultant signature datasets (Hindi script signature and English script signatures) separately. The modified gradient feature and SVM classifier were employed for identification and verification purposes. To the best of authors' knowledge, the multi-script signature identification and verification has never been used for the task of signature verification and this is the first report of using Hindi and English signatures in this area. Two different results for identification and verification are calculated and analysed. The accuracy of 98.05% is obtained for the identification of signature script using 2160 (1080 Hindi + 1080 English) samples for training and 1080 (540 Hindi + 540 English) samples for testing. The resultant data sets obtained in script identification of signatures were used for verification purpose. The FRR, FAR for Hindi and English was obtained 8.0%, 4.0% and 12.0%, 10.0% respectively.