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<p><b>Abstract</b>—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.</p>
Hand geometry, classification, verification, biometric systems, Euclidean distance, Hamming distance, Gaussian mixture models, radial basis functions.

R. Sanchez-Reillo, A. Gonzalez-Marcos and C. Sanchez-Avila, "Biometric Identification through Hand Geometry Measurements," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 22, no. , pp. 1168-1171, 2000.
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