"Performance of an Off-Line Signature Verification Method Based on Text" by Srikanta Pal, Alireza Alaei et al.
 

Performance of an Off-Line Signature Verification Method Based on Texture Features on a Large Indic-Script Signature Dataset

Document Type

Conference Article

Publication Title

Proceedings - 12th IAPR International Workshop on Document Analysis Systems, DAS 2016

Abstract

In this paper, a signature verification method based on texture features involving off-line signatures written in two different Indian scripts is proposed. Both Local Binary Patterns (LBP) and Uniform Local Binary Patterns (ULBP), as powerful texture feature extraction techniques, are used for characterizing off-line signatures. The Nearest Neighbour (NN) technique is considered as the similarity metric for signature verification in the proposed method. To evaluate the proposed verification approach, a large Bangla and Hindi off-line signature dataset (BHSig260) comprising 6240 (260×24) genuine signatures and 7800 (260×30) skilled forgeries was introduced and further used for experimentation. We further used the GPDS-100 signature dataset for a comparison. The experiments were conducted, and the verification accuracies were separately computed for the LBP and ULBP texture features. There were no remarkable changes in the results obtained applying the LBP and ULBP features for verification when the BHSig260 and GPDS-100 signature datasets were used for experimentation.

First Page

72

Last Page

77

DOI

10.1109/DAS.2016.48

Publication Date

6-10-2016

Comments

Open Access; Green Open Access

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