Offline Signature Verification Using Textural Descriptors
What is it about?
Offline signature verification has been the most commonly employed modality for authentication of an individual and, it enjoys global acceptance in legal, banking and official documents. Verifying the authenticity of a signature (genuine or forged) remains a challenging problem from the perspective of computerized solutions. This paper presents a signature verification technique that exploits the textural information of a signature image to discriminate between genuine and forged signatures. Signature images are characterized using two textural descriptors, the local ternary patterns (LTP) and the oriented basic image features (oBIFs). Signature images are projected in the feature space and the distances between pairs of genuine and forged signatures are used to train SVM classifiers (a separate SVM for each of the two descriptors). When presented with a questioned signature, the decision on its authenticity is made by combining the decisions of the two classifiers. The technique is evaluated on Dutch and Chinese signature images of the ICDAR 2011 benchmark dataset and high accuracies are reported.
The following have contributed to this page: Dr Mouloud AYAD
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