Hand recognition using geometric classifiers

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Abstract

We discuss the issues and challenges in the design of a hand outline based recognition system. Our system is easier to use, cheaper to build and more accurate than previous systems. Extensive tests on more than 700 images collected from 70 people are reported. Classification, verification and identification of the input images were done using two simple geometric classifiers. We describe a novel minimum enclosing ball classifier which performs well for hand recognition and could be of interest for other applications. © Springer-Verlag Berlin Heidelberg 2004.

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APA

Bulatov, Y., Jambawalikar, S., Kumar, P., & Sethia, S. (2004). Hand recognition using geometric classifiers. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3072, 753–760. https://doi.org/10.1007/978-3-540-25948-0_102

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