A Novel Illumination Compensation Method Using Wavelet Packet Transformation

Article Preview

Abstract:

A novel illumination compensate method is proposed in this paper to improve recognition performance. A modified lighting model called Lambertin which includes additive noise and multiplicative noise are presented firstly. Then, additive noise is removed by using wavelet packet transformation. Next, the processed image is transformed into logarithm domain and the multiplicative noise, which has been named additive noise, is removed by means of the same above algorithm. Finally, a compensated face image is obtained. We examine the proposed method on Yale extended B database compared with other methods. Experimental results show that our algorithm improves by 3%~12% recognition rate. It can effectively adjust the facial images for varying illumination conditions and also improve the recognition performance and robustness.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 317-319)

Pages:

897-900

Citation:

Online since:

August 2011

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2011 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] ZHUANG L SH. Research on key algorithms for face recognition under complex illumination [D].Hefei: University of Science and Technology of China, 2006.(in Chinese)

Google Scholar

[2] ISH IYAMA R, SAKAMOTO S. Geodesic illumination basis: compensating for illumination variations in any pose for face recognition [C]. Proceeding of 16th Internat. Conf. Pattern recognition, 2002: 2972301.

DOI: 10.1109/icpr.2002.1047455

Google Scholar

[3] LEE S W, MOON S H, LEE S W. Face recognition under arbitrary illumination using illuminated exemplars [J]. Pattern Recognition, 2007, 40(5): 160521620.

DOI: 10.1016/j.patcog.2006.09.016

Google Scholar

[4] MOSES Y, ULLMAN S. Limitation of nonmodel-based recognition schemes[C] .Proceeding of ECCV292, Berlin: Springer Verlag, 1992: 8202828.

Google Scholar

[5] YAO J M, XU T F, NI G Q. Nonlinear target tracking method based on optimized wavelet features [J]. Opt. Precision Eng . , 2007, 15(3): 4282433. ( in Chinese)

Google Scholar

[6] SAVVIDESM, KUMARV. Illumination normalization using logarithm transform for face recognition[C] . Proceeding of IAPRAVBPA, 2010: 5492556.

Google Scholar

[7] XIE X D, LAMKM. Face recognition under varying illumination based on a 2D face shape model[J] . Pattern Recognition, 2009, 38(2) : 2212230.

DOI: 10.1016/s0031-3203(04)00275-4

Google Scholar

[8] ZHU JH , LIUB, SCHWARTZSC. General illumination correction and its application to face recognition[ C] .Proceeding of IEEE OCASSSP , 2003: 1332136.

Google Scholar