Date of Publication :10th February 2018
Abstract: +Palm-print is another biometric strategy to recognize a person. The featuresin a palm-print incorporate principle lines, wrinkles also, ridges, and so on. Line structure feature, which incorporates principal lines and wrinkles, is one of the most well-known techniques in palm-print recognition. Be that as it may, the line structure include doesn't contain the thickness and width data of principal lines and wrinkles, which are essential to segregate palm-prints. Ridges are excluded from line structure feature either. So these techniques can't recognize palm-prints having comparative tine structure. Besides, the line extraction is a tedious task. The fact that head-lines, wrinkles and ridges have different resolutions inspires us to analyze the palm-print utilizing multi-resolution examination strategy. An epic palm-print feature, named wavelet energyfeatures, is characterized utilizing wavelet, which is a powerful apparatus of multi-goals investigation. In this paper, WEF can reflect the wavelet energy circulation of the principal lines, wrinkles and ridges in several directions at various wavelet decomposition level, so its function to separate palms is good. Effortlessness to process is another quality of WEF. The high recognition rates got in experiments appears the impact of the proposed technique.
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