Robust palmprint verification using sparse representation of binarized statistical features: a comprehensive study

This paper proposes a new scheme for robust palmprint verification using sparse representation of Binarized Statistical Image Features (BSIF). Since palmprint comprises of rich set of features including principal lines, ridges and wrinkles, the use of appropriate texture descriptor is expected to accurately capture these information. To this extent, we explore the BSIF texture descriptor which codes each pixel of the given palmprint image in terms of binary strings based on the filter response. The BSIF learns the filter basis from the natural images by exploring statistical independence. We then use the Sparse Representation Classifier (SRC) on these BSIF features to perform the subject verification. Extensive experiments are carried out on three different large scale publically available palmprint databases. We then present an extensive analysis by comparing the proposed scheme with five different contemporary state-of-the-art schemes that reveals the outstanding performance.

[1]  David Zhang,et al.  Palmprint identification using feature-level fusion , 2006, Pattern Recognit..

[2]  Jifeng Dai,et al.  Multifeature-Based High-Resolution Palmprint Recognition , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Bin Li,et al.  Palmprint Identification using Boosting Local Binary Pattern , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[4]  Helen C. Shen,et al.  Palmprint identification using palmcodes , 2004, Third International Conference on Image and Graphics (ICIG'04).

[5]  Murat Ekinci,et al.  Gabor-based kernel PCA for palmprint recognition , 2007 .

[6]  Chin-Chuan Han,et al.  Personal authentication using palm-print features , 2003, Pattern Recognit..

[7]  Zhenhua Guo,et al.  Online joint palmprint and palmvein verification , 2011, Expert Syst. Appl..

[8]  David Zhang,et al.  Online Palmprint Identification , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Guillermo Sapiro,et al.  Online Learning for Matrix Factorization and Sparse Coding , 2009, J. Mach. Learn. Res..

[10]  David Zhang,et al.  Fisherpalms based palmprint recognition , 2003, Pattern Recognit. Lett..

[11]  Ashok Rao,et al.  A Novel Three Stage Process for Palmprint Verification , 2009, 2009 International Conference on Advances in Computing, Control, and Telecommunication Technologies.

[12]  Esa Rahtu,et al.  BSIF: Binarized statistical image features , 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

[13]  David Zhang.  Palmprint Authentication , 2004, International Series on Biometrics.

[14]  A. Teoh,et al.  Palmprint Recognition with PCA and ICA , 2003 .

[15]  Ramachandra Raghavendra,et al.  Novel image fusion scheme based on dependency measure for robust multispectral palmprint recognition , 2014, Pattern Recognit..

[16]  Ramachandra Raghavendra,et al.  Designing efficient fusion schemes for multimodal biometric systems using face and palmprint , 2011, Pattern Recognit..

[17]  Hong Wang,et al.  Improved Competitive Code for Palmprint Recognition Using Simplified Gabor Filter , 2009, ICIC.

[18]  Zohaib Khan,et al.  Contour Code: Robust and efficient multispectral palmprint encoding for human recognition , 2011, 2011 International Conference on Computer Vision.

[19]  Ajay Kumar,et al.  Incorporating Cohort Information for Reliable Palmprint Authentication , 2008, 2008 Sixth Indian Conference on Computer Vision, Graphics & Image Processing.