Abstract
In this paper, we describe an application of biometric recognition that is structured basically with three inputs: the hand geometry, voice and image. The hand geometry is given by an image of “the palm” of the hand with a 480x640 size which is preprocessed with a feature extraction that uses computer vision techniques and with certain features we recognize the individual. After that we preprocessed the image and get some variables as the fingers, palm, wrist, also a segment of the palm; they appear to be from a with a fuzzy system that will tell us how much they seemed to a certain person, comparing each variable given by the preprocessing of the image according to the data base that its already stored (all the images of the individuals, voice, etc.).
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Salazar-Tejeda, P.A., Melin, P., Castillo, O. (2008). A New Biometric Recognition Technique Based on Hand Geometry and Voice Using Neural Networks and Fuzzy Logic. In: Castillo, O., Melin, P., Kacprzyk, J., Pedrycz, W. (eds) Soft Computing for Hybrid Intelligent Systems. Studies in Computational Intelligence, vol 154. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70812-4_10
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DOI: https://doi.org/10.1007/978-3-540-70812-4_10
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