In slap fingerprint segmentation, crease is the most difficult edge to correctly detect. In this paper, we present a novel yet simple and accurate algorithm for the principal axis and crease detection. Firstly, the principal axis of each foreground region is detected using the minimal rotational inertia; Secondly, the crease detection is done based on cost function minimization. This algorithm has been incorporated in a slap fingerprint segmentation scheme, previously developed by the authors, producing successful results. © 2010 IEEE.
CITATION STYLE
Zhang, Y. L., Li, Y. M., Wu, H. T., Huang, Y. P., Xiao, G., & Gao, F. (2010). Principal axis and crease detection for slap fingerprint segmentation. In Proceedings - International Conference on Image Processing, ICIP (pp. 3081–3084). https://doi.org/10.1109/ICIP.2010.5654266
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