Journal
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
Volume 22, Issue 10, Pages 1168-1171Publisher
IEEE COMPUTER SOC
DOI: 10.1109/34.879796
Keywords
hand geometry; classification; verification; biometric systems; Euclidean distance; Hamming distance; Gaussian mixture models; radial basis functions
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A work in defining and implementing a biometric system based on hand geometry identification is presented here. Hand features are extracted from a color photograph taken when the user has placed his hand on a platform designed for such a task. Different pattern recognition techniques have been tested to be used in classification and/or verification from Euclidean distance to neural networks. Experimental results, up to a 97 percent rate of success in classification. will show the possibility of using this system in medium/high security environments with full acceptance from all users.
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