Abstract
In this paper, a novel iris recognition method is proposed based on a state-of-the-art classification technique called minimax probability machine (MPM). Engaging the binary MPM technique, this work develops a multi-class MPM classification for reliable iris recognition with high accuracy. The experiments on iris database demonstrate that compared to the existent methods, the MPM-based iris recognition algorithm obtains better classification performance. It can significantly improve the recognition accuracy and has a competitive and promising performance.
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Wang, Y., Han, Jq. (2006). Minimax Probability Machine for Iris Recognition. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760023_6
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DOI: https://doi.org/10.1007/11760023_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34437-7
Online ISBN: 978-3-540-34438-4
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