Proposed Multi-Modal Palm Veins-Face Biometric Authentication

Biometric authentication technology identifies people by their unique biological information. An account holder’s body characteristics or behaviors are registered in a database and then compared with others who may try to access that account to see if the attempt is legitimate. Since veins are internal to the human body, its information is hard to duplicate. Compared with a finger or the back of a hand, a palm has a broader and more complicated vascular pattern and thus contains a wealth of differentiating features for personal identification. However, a single biometric is not sufficient to meet the variety of requirements, including matching performance imposed by several large-scale authentication systems. Multi-modal biometric systems seek to alleviate some of the drawbacks encountered by uni-modal biometric systems by consolidating the evidence presented by multiple biometric traits/sources. This paper proposes a multi-modal authentication technique based on Palm Veins as a personal identifying factor, augmented by face features to increase the accuracy of security recognition. The obtained results point at an increased authentication accuracy.

[1]  Toshio Endoh,et al.  Palm vein authentication technology and its applications , 2005 .

[2]  Bo Zhao,et al.  Research on Traffic Number Recognition Based on Neural Network and Invariant Moments , 2007, 2007 International Conference on Machine Learning and Cybernetics.

[3]  Jinsong Leng,et al.  Analysis of Hu's moment invariants on image scaling and rotation , 2010, 2010 2nd International Conference on Computer Engineering and Technology.

[4]  Xiaoou Tang,et al.  Texture information in run-length matrices , 1998, IEEE Trans. Image Process..

[5]  Baharum Baharudin,et al.  The Statistical Quantized Histogram Texture Features Analysis for Image Retrieval Based on Median and Laplacian Filters in the DCT Domain , 2013, Int. Arab J. Inf. Technol..

[6]  Tai-hoon Kim,et al.  Palm Vein Authentication System: A Review , 2010 .

[7]  Aamir Khan,et al.  Principal Component Analysis-Linear Discriminant Analysis Feature Extractor for Pattern Recognition , 2012, ArXiv.

[8]  Ajay Kumar,et al.  Contactless palm vein identification using multiple representations , 2010, 2010 Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS).

[9]  Alaa Eleyan,et al.  Co-occurrence matrix and its statistical features as a new approach for face recognition , 2011, Turkish Journal of Electrical Engineering and Computer Sciences.

[10]  F. Albregtsen Statistical Texture Measures Computed from Gray Level Coocurrence Matrices , 2008 .

[11]  Marzuki Khalid,et al.  Multimodal face and finger veins biometric authentication , 2010 .

[12]  Qin Li,et al.  Palm Vein Extraction and Matching for Personal Authentication , 2007, VISUAL.