Analysis on Feature Extraction of Periocular Region(Soft biometrics) using LBP, PCA, ICA & Gabour filters

  IJCOT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© - June Issue 2013 by IJCTT Journal
Volume-4 Issue-6                           
Year of Publication : 2013
Authors :Sunila Godara, Vanita Rawal, Megha Ranolia

MLA

Sunila Godara, Vanita Rawal, Megha Ranolia"Analysis on Feature Extraction of Periocular Region(Soft biometrics) using LBP, PCA, ICA & Gabour filters"International Journal of Computer Trends and Technology (IJCTT),V4(6):1777-1782 June Issue 2013 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract: - In this paper we analyses the various methods of feature extraction. In iris recognition there are several steps to perform identification. Similarly these steps are used in periocular region i.e. defined as the fixed region surrounding the iris of the individual. This region encompasses the eyelids, eyelashes, eyebrows and the surrounding skin area. LBP is defined as Local Binary Pattern used for feature extraction. The LBP features are firstly extracted from the original facial expression images. The LBP operator was introduced as a complementary measure for local image contrast, and it was developed as a grayscale invariant pattern measure adding harmonizing information to the “amount” of texture in images. The independent component analysis (ICA) is a technique that extracts the original signals from mixtures of many independent sources without a priori information on the sources and the process of the mixture. Gabor features encode facial shape over a broader range of scales. In the commonly adopted PCA representation, the pixel grey values are normalized based on equalized value of histogram, to have a mean of zero and a standard deviation of one.

 

References-
[1] Damon L. Woodard Shrinivas Pundlik Philip Miller . “On the Fusion of Periocular and Iris Biometrics in Non-ideal Images”, In proceeding of 20th International Conference on Pattern Recognition, Istanbul, Turkey, August 2010, pp. 23-26.
[2] U. Park, A. Ross, and A.K. Jain, “Periocular Biometrics in the Visible Spectrum: a Feasibility Study”, in Proceedings of the 3rd IEEE International Conference on Biometrics: Theory, Applications and systems, 2009, pp. 153–158.
[3] Ashish Kumar Dewangan, Majid Ahmed Siddhiqui , Iris Recognition - An Efficient Biometric for Human Identification and Verification,1:2249-8958, 2012.
[4] S. Baker, K. W. Bowyer, and P. J. Flynn, “Empirical evidence for correct iris match score degradation with increased time-lapse between gallery and probe matches,”in Proc. Int. Conf. on Biometrics, pp. 1170-1179, 2009.
[5] Zhu E., Yin J., and Zhang G., “Fingerprint Matching Based on Global Alignment of Multiple Reference Minutiae,” Computer Journal of Pattern Recognition, vol. 38 no. 10, pp. 1685-1694, 2005.
[6] A.K.Jain and U. Park. Facial marks: soft biometric for face recognition. In ICIP, 2009.
[7] C. Sanchez-Avila , R. Sanchez-Reillo, “Two different approaches for iris recognition using Gabor filters and multiscale zero-crossing representation”, The journal of pattern recognization society, 23 July 2005, pp.231-240.
[8] Jie Zou, “A Comparative Study of Local Matching Approach for Face Recognition”, IEEE Transactions on Image Processing, Vol. 16, No. 10, October 2007, pp. 2617-2628.
[9] XIAO-FENG GU JIN-XIN SHI “The Comparison of Iris Recognition Using Principal Component Analysis,Independent Component Analysis and Gabor Wavelets”, Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference, 9-11 July 2010 pp.:61 – 64
[10]Institute of Automation Chinese Academy of Sciences. Database of CASIA iris image [EB/OL].

Keywords - LBP, ICA, PCA, Gabor Filters, Periocular region