One-Class Writer-Independent Offline Signature Verification Using Feature Dissimilarity Thresholding

Abstract

Usual handwritten signature verification systems address the writer-independent (WI) approach using only bi-class robust classifiers to deal with the most challenging tasks. Indeed, WI concept, the reduced size of references and one-class signature verification are still open issues in practical cases. In this paper, we propose a one-class WI system using feature dissimilarity measures thresholding for classification and a reduced number of references. The proposed system involves the use of contourlet transform-based directional code co-occurrence matrix feature generation method. The verification is achieved through a WI threshold which is automatically selected using a new signature stability criterion. The proposed WI concept is besides addressed through the mixture of different writers’ data sets in both the design and verification stages. Experimental results show the effectiveness of the proposed system in spite of the strict verification protocol using the one-class concept, a unique threshold for accepting or rejecting a questioned signature, the reduced number of writers, and the limited number of reference signatures.