Abstract
Hand geometry based biometric verification has proven to be the most suitable and acceptable biometrics trait for medium and low security applications. Hereby a new approach for the personal identification using hand images is presented. Two kinds of biometric indicators are extracted from the low-resolution hand images; (i) palmprint features, which are composed of principal lines, wrinkles, minutiae, delta points, etc., and (ii) hand geometry features which include area/size of palm, length and width of fingers. In the article we focus on feature extraction methods applied to one-sensor multimodal hand-palm biometrics system.
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Choraś, R.S., Choraś, M. (2007). Multimodal Hand-Palm Biometrics. In: Beliczynski, B., Dzielinski, A., Iwanowski, M., Ribeiro, B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2007. Lecture Notes in Computer Science, vol 4432. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71629-7_46
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DOI: https://doi.org/10.1007/978-3-540-71629-7_46
Publisher Name: Springer, Berlin, Heidelberg
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