Hand-Dorsa Vein Recognition Based on Scale and Contrast Invariant Feature Matching
Author:
Affiliation:
1. Xuhai College, China University of Mining and Technology
2. School of Electrical and Power Engineering, China University of Mining and Technology
3. School of Information and Control Engineering, China University of Mining and Technology
Publisher
Institute of Electronics, Information and Communications Engineers (IEICE)
Subject
Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software
Link
https://www.jstage.jst.go.jp/article/transinf/E100.D/12/E100.D_2017EDL8103/_pdf
Reference4 articles.
1. [1] W. Yang, G. Ma, W. Li, and Q. Liao, “Finger Vein Verification Based on Neighbor Pattern Coding,” IEICE Trans. Inf. & Syst., vol.E96-D, no.5, pp.1227-1229, May 2013. 10.1587/transinf.e96.d.1227
2. [2] S. Stanciu, D. Tranca, and D. Coltuc, “Contrast enhancement influences the detection of gradient based local invariant features and the matching of their descriptors,” J VIS COMMUN IMAGE R., vol.32, pp.246-256, Oct. 2015. 10.1016/j.jvcir.2015.08.008
3. [3] J. Wang, G. Wang, M. Li, K. Wang, and H. Tian, “Hand vein recognition based on improved template matching,” Int. J. Bioautomation., vol.18, no.4, pp.337-348, Dec. 2014.
4. [4] W. Kang, Y. Liu, Q, Wu, X. Yue, and T. Wennekers, “Contact-Free Palm-Vein Recognition Based on Local Invariant Features,” PLOS ONE., vol.9, no.5, pp.1-12, May 2014. 10.1371/journal.pone.0097548
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