Abstract
In recent years, the hand dorsal vein has received increasing attentions in the domain of biometrics. This paper presents a novel approach for hand dorsal vein identification based on shape description of the venous network. In order to generate robust data for shape feature extraction, an effective segmentation method is first proposed which makes use of the enhanced detail of blood vessels. The global and local shape representation are then hierarchically combined according to a coarse-to-fine strategy to encode the distinctiveness. The global one is described as the graph composed by endpoints and crossing points of the skeleton of the vein regions; while the local one is represented by a patch based binary coding scheme. The proposed method was evaluated on the NCUT database that contains 2,040 hand dorsal vein (Near Infrared) images of 102 subjects and achieved a rank-one recognition rate of 98.53%, clearly highlighting its effectiveness.
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Zhu, X., Huang, D., Wang, Y. (2013). Hand Dorsal Vein Recognition Based on Shape Representation of the Venous Network. In: Huet, B., Ngo, CW., Tang, J., Zhou, ZH., Hauptmann, A.G., Yan, S. (eds) Advances in Multimedia Information Processing – PCM 2013. PCM 2013. Lecture Notes in Computer Science, vol 8294. Springer, Cham. https://doi.org/10.1007/978-3-319-03731-8_15
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DOI: https://doi.org/10.1007/978-3-319-03731-8_15
Publisher Name: Springer, Cham
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