Palmprint verification using SIFT majority voting
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CitationAbeysundera, H. P. & Eskil, M. T. (2012). Palmprint verification using SIFT majority voting. Paper presented at the Computer and Information Sciences II, 291-297. doi:10.1007/978-1-4471-2155-8-37
In this paper we illustrate the implementation of a robust, real-time biometric system for identity verification based on palmprint images. The palmprint images are preprocessed to align the major axes of hand shapes and to extract the palm region. We extract features using Scale Invariant Feature Transform (SIFT). Classification of individual SIFT features is done through KNN. The class of the hand image is decided by a majority based voting among its classified SIFT features. We demonstrate on the CASIA and PolyU datasets that the proposed system achieves authentication accuracy comparable to other state of the art algorithms.