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Biometric Identification through Hand Geometry Measurements
October 2000 (vol. 22 no. 10)
pp. 1168-1171

Abstract—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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Index Terms:
Hand geometry, classification, verification, biometric systems, Euclidean distance, Hamming distance, Gaussian mixture models, radial basis functions.
Citation:
Raul Sanchez-Reillo, Carmen Sanchez-Avila, Ana Gonzalez-Marcos, "Biometric Identification through Hand Geometry Measurements," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 10, pp. 1168-1171, Oct. 2000, doi:10.1109/34.879796
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