Abstract
The segmentation of fingerprint images is an important step in an automatic fingerprint identification system (AFIS). It is used to identify the foreground of a fingerprint image. Existing methods are usually based on some point features such as average gray level, variance, Gabor response, etc, while they ignored the local information of foreground regions. In this paper, a novel segmentation approach is proposed based on the mean shift algorithm, which not only take advantage of the traditional features, but also use the local information. In order to segment the fingerprint image better, we modified the original mean shift segmentation algorithm. First we calculate some effective features of fingerprint images and determine the parameters adaptively, and then we process the image based on the mean shift algorithm and get some divided regions, finally the foreground are selected from these regions. The accuracy and effectiveness of our method are validated by experiments performed on FVC database.
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Xue, Z., Zhao, T., Wu, M., Guo, T. (2012). A Novel Segmentation Algorithm of Fingerprint Images Based on Mean Shift. In: Huang, DS., Gupta, P., Zhang, X., Premaratne, P. (eds) Emerging Intelligent Computing Technology and Applications. ICIC 2012. Communications in Computer and Information Science, vol 304. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31837-5_30
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DOI: https://doi.org/10.1007/978-3-642-31837-5_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31836-8
Online ISBN: 978-3-642-31837-5
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