title: Finger vein recognition with personalized feature selection.
abstract: Finger veins are a promising biometric pattern for personalized identification in terms of their advantages over existing biometrics. Based on the spatial pyramid representation and the combination of more effective information such as gray, texture and shape, this paper proposes a simple but powerful feature, called Pyramid Histograms of Gray, Texture and Orientation Gradients (PHGTOG). For a finger vein image, PHGTOG can reflect the global spatial layout and local details of gray, texture and shape. To further improve the recognition performance and reduce the computational complexity, we select a personalized subset of features from PHGTOG for each subject by using the sparse weight vector, which is trained by using LASSO and called PFS-PHGTOG. We conduct extensive experiments to demonstrate the promise of the PHGTOG and PFS-PHGTOG, experimental results on our databases show that PHGTOG outperforms the other existing features. Moreover, PFS-PHGTOG can further boost the performance in comparison with PHGTOG.
authors: School of Computer Science and Technology, Shandong University, Jinan 250101, China. fyzq10@126.com
authors: Xiaoming
authors: X
authors: Xi
authors: Gongping
authors: G
authors: Yang
authors: Yilong
authors: Y
authors: Yin
authors: Xianjing
authors: X
authors: Meng
mesh_terms: D000465:Algorithms; D001699:Biometry / Q000379:methods*; D005385:Fingers / Q000098:blood supply*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D010781:Photography / Q000379:methods*; D011996:Records; D013382:Subtraction Technique; D014680:Veins / Q000033:anatomy & histology*
references: IEEE Trans Image Process. 2012 Apr;21(4):2228-44
references: 21997267
references: Sensors (Basel). 2011;11(3):2319-33
references: 22163741
references: Sensors (Basel). 2012;12(2):1738-57
references: 22438735
references: Interdiscip Sci. 2009 Dec;1(4):280-9
references: 20640806
references: Sensors (Basel). 2011;11(12):11357-71
references: 22247670
references: Appl Opt. 2002 Dec 10;41(35):7429-36
references: 12502300