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Handwritten signature is one of the oldest biometric attributes used for authentication of an individual or a document. The purpose of this study is to present an empirical contribution towards the understanding of signature verification using a novel method involving off-line Hindi (Devnagari) signatures. Although research in the field of signature verification involving Western signatures has been well studied, there has been relatively little attention devoted to non-Western signatures such as Chinese, Japanese, Arabic, Persian etc. In this study, the performance of an off-line signature verification system involving Hindi signatures, whose style is distinct from Western scripts, was investigated. The gradient feature, Zernike moment features and SVMs were considered for verification. To the best of the authors' knowledge, Hindi signatures investigated as part of a large dataset have never been used for the task of signature verification, and this research work is only the second important report using Hindi signatures in this area. An encouraging accuracy of 90.69% was obtained using gradient feature. The Hindi signature database employed for experimentation consisted of 2400 (100 × 24) genuine signatures and 3000 (100 × 30) forgeries. The error rates of 11.50% FRR and 7.12% FAR were obtained through experimentation using gradient features.