Sliding Window Based Fast Corner Matching Palmprint Authentication

Authentication time is the main and important part of the authentication system. Normally the response time should be fast but as the number of persons in the database increases, there is probability of more response time taken for authentication. The need of fast authentication system arises so that authentication time matching time is very less. This paper proposes a sliding window approach to make fast authentication system. The highlight of sliding window method is constant matching time, fast and can match translated images also. Several palmprint matching methods like match by correlation etc. are dependent upon the number of corners detected and so is the matching time. In sliding window method, matching time is constant as the numbers of matching operations are limited and the matching time is independent of the number of corners detected. The palmprint corner features extracted using two approaches Phase Congruency Corner Detector and Harris Corner Detector are binarized so that only useful information features is matched. The two approaches of Phase Congruency Corner Detector and Harris Corner Detector, when matched with hamming distance using sliding window can achieve recognition rate of 97.7% and 97.5% respectively.

[1]  D Marr,et al.  Theory of edge detection , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[2]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Christopher G. Harris,et al.  A Combined Corner and Edge Detector , 1988, Alvey Vision Conference.

[4]  S. Foguel.  A new approach to the study of Harris type Markov operators , 1989 .

[5]  Peter Kovesi,et al.  Image Features from Phase Congruency , 1995 .

[6]  David Zhang,et al.  Two novel characteristics in palmprint verification: datum point invariance and line feature matching , 1999, Pattern Recognit..

[7]  David Zhang,et al.  Automated Biometrics: Technologies and Systems , 2000 .

[8]  Sharath Pankanti,et al.  Biometrics: The Future of Identification - Guest Editors' Introduction , 2000, Computer.

[9]  P. Jonathon Phillips,et al.  An Introduction to Evaluating Biometric Systems , 2000, Computer.

[10]  David Zhang,et al.  Automatic Palmprint Verification , 2001, Int. J. Image Graph..

[11]  David Zhang,et al.  WAVELET BASED PALMPRINT RECOGNITION , 2002 .

[12]  David Zhang,et al.  Palmprint Identification by Fourier Transform , 2002, Int. J. Pattern Recognit. Artif. Intell..

[13]  David Zhang,et al.  Palmprint recognition using eigenpalms features , 2003, Pattern Recognit. Lett..

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

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

[16]  Max-Olivier Hongler,et al.  The Resonant Retina: Exploiting Vibration Noise to Optimally Detect Edges in an Image , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[17]  Niels Chr. Overgaard.  On a Modification to the Harris Corner Detector , 2003 .

[18]  Arun Ross,et al.  An introduction to biometric recognition , 2004, IEEE Transactions on Circuits and Systems for Video Technology.

[19]  David Zhang,et al.  Palmprint classification using principal lines , 2004, Pattern Recognit..

[20]  David Zhang,et al.  Texture-based palmprint retrieval using a layered search scheme for personal identification , 2005, IEEE Transactions on Multimedia.

[21]  David Zhang,et al.  Personal authentication using multiple palmprint representation , 2005, Pattern Recognit..

[22]  Bülent Sankur,et al.  Hand biometrics , 2006, Image Vis. Comput..

[23]  Helen C. Shen,et al.  Personal authentication using hand images , 2006, Pattern Recognit. Lett..

[24]  Toufik Taibi.  Design Pattern Formalization Techniques , 2007 .

[25]  Johan A. K. Suykens,et al.  Kernel Clustering for Knowledge Discovery in Clinical Microarray Data Analysis , 2007 .

[26]  Nikola Pavesic,et al.  Personal recognition based on an image of the palmar surface of the hand , 2007, Pattern Recognit..

[27]  David Zhang,et al.  Palmprint verification based on principal lines , 2008, Pattern Recognit..

[28]  L. Souza,et al.  Capturing Data in Healthcare Using Patient-Centered Mobile Technology , 2008 .

[29]  F. Nielsen.  Harris-Stephens' combined corner/edge detector , 2008 .

[30]  Gheorghita Ghinea,et al.  User Centered Design for Medical Visualization , 2008 .

[31]  Yodchanan Wongsawat,et al.  Palmprint image enhancement using phase congruency , 2009, 2008 IEEE International Conference on Robotics and Biomimetics.

[32]  Vitomir Struc,et al.  Phase congruency features for palm-print verification , 2009 .

[33]  Albert-Jan Boonstra,et al.  Low frequency array (lofar)- potential and challenges , 2010 .

[34]  Roger J. Green,et al.  Applied Signal and Image Processing: Multidisciplinary Advancements , 2011 .

[35]  Changsheng Xu,et al.  Generative Group Activity Analysis with Quaternion Descriptor , 2011, MMM.

[36]  Xiao Bai,et al.  Graph-Based Methods in Computer Vision: Developments and Applications , 2012 .

[37]  Hanêne Ben-Abdallah,et al.  An Improved Lane Detection and Tracking Method for Lane Departure Warning Systems , 2013, Int. J. Comput. Vis. Image Process..