Finger Vein verification using local histogram of hybrid texture descriptors

Lately, finger vein has been recognized as an efficacious biometric method for user authentication due to the uniqueness of vein patterns and its insusceptibility to forgery because the vein patterns reside inside the human body. In this work, hybrid histogram descriptor is the proposed method. This method utilizes the sign and magnitude components of the texture extracted by using Binary Gradient Contour (BGC). Subsequently, the histogram is locally computed to determine the weight distribution of the sign and magnitude value for the hybrid texture descriptors. The extensive experimental results demonstrate the overall superiority of the proposed method with the EER as low as 0.353%.

[1]  Chengbo Yu,et al.  Finger-vein image recognition combining modified hausdorff distance with minutiae feature matching , 2009 .

[2]  Kang Ryoung Park,et al.  Finger vein recognition using minutia-based alignment and local binary pattern-based feature extraction , 2009 .

[3]  Naoto Miura,et al.  Extraction of Finger-Vein Patterns Using Maximum Curvature Points in Image Profiles , 2007, MVA.

[4]  J. Shao.  Linear Model Selection by Cross-validation , 1993 .

[5]  Yanzhe Cui,et al.  Finger-vein image recognition combining modified Hausdorff distance with minutiae feature matching , 2009, Interdisciplinary Sciences: Computational Life Sciences.

[6]  Zhenhua Guo,et al.  A Completed Modeling of Local Binary Pattern Operator for Texture Classification , 2010, IEEE Transactions on Image Processing.

[7]  Eui Chul Lee,et al.  New Finger Biometric Method Using Near Infrared Imaging , 2011, Sensors.

[8]  Shahrel Azmin Suandi,et al.  Finger Vein Recognition Using Local Line Binary Pattern , 2011, Sensors.

[9]  Martin R. Varley,et al.  Hand vein recognition based on multiple keypoints sets , 2012, 2012 5th IAPR International Conference on Biometrics (ICB).

[10]  Naoto Miura,et al.  Feature Extraction of Finger-vein Patterns Based on Repeated Line Tracking and Its Application to Personal Identification , 2022 .

[11]  Francesco Bianconi,et al.  Image classification with binary gradient contours , 2011 .

[12]  Wenxin Li,et al.  Finger-Vein Authentication Based on Wide Line Detector and Pattern Normalization , 2010, 2010 20th International Conference on Pattern Recognition.