Abstract
In this paper an efficient fully automatic method for finger vein pattern extraction is presented using the second order local structure of infrared images. In a sequence of processes, the veins structure is normalized and enhanced, eliminating also the fingerprint lines using wavelet decomposition methods. A compound filter which handles the second order local structure and exploits the multidirectional matching filter response in the direction of the smallest curvature is used in order to enrich the vein patterns. Edge suppression decreases the misclassified edges as veins in the forthcoming crisp clustering step. In a postprocessing module, a morphological majority filter is applied in the segmented image to smooth the contours and to remove some small isolated regions and a reconstruction process reduces the outliers in the finger vein pattern. The proposed method was evaluated in a small database of infrared images giving excellent detection accuracy of vein patterns.
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Vlachos, M., Dermatas, E. (2008). Vein Segmentation in Infrared Images Using Compound Enhancing and Crisp Clustering. In: Gasteratos, A., Vincze, M., Tsotsos, J.K. (eds) Computer Vision Systems. ICVS 2008. Lecture Notes in Computer Science, vol 5008. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79547-6_38
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DOI: https://doi.org/10.1007/978-3-540-79547-6_38
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