第5卷第4期 智能系统学报 Vol.5 No.4 2010年8月 CAAI Transactions on Intelligent Systems Aug.2010 doi:10.3969/j.issn.1673-4785.2010.04.000 A new illumination preprocessing method for face recognition GAN Sheng College of Information Science and Technology,Nankai University,Tianjin 300071,China) Abstract:Differences in illumination of the same face can defeat simple face recognition systems,yet most methods that compensate are too difficult to implement.Local quotient image (LQI)is an efficient illumination preprocessing method for face recognition systems.An illumination model and a face model were developed,and their use in the new method was analyzed in detail.Analysis of the methods computational complexity showed it to be efficient.Experimental results on Yale Face Database B showed that the method can effectively eliminate the effects of differences in illumination and provides considerable improvement in recognition rates. Keywords:face recognition;illumination preprocessing;local quotient image;illumination model CLC Number:TP391.41 Document code:A Article ID:1673-4785(2009)06-0549-12 Face recognition has become one of the most suc- conests] symmetric shape-from-shading,quotient cessful applications of image analysis and understand- image,gamma intensity correctionsf quotient ing as a result of significant rescarch work in the last image,eigenphases,histogram equalization and decade2.However,variations in the quality of ima- logarithm tranforGood results have been repor ges heavily affect the performance of current face rec- ted by all these methods.However,some of these ognition systems.Experiments done on the Facial Rec- methods require other images of the same person under ognition Technology (FERET)database and the Face different illumination conditions and some have a com- Recognition Vendor Test 2000 (FRVT2000)tests paratively high computational complexity which makes showed that variations in illumination are among the them impractical.For example,Shape-From-Shading, bottlenecks for a practical face recognition system Quotient Image,Illumination Cones all require more Face appearance can change dramatically due to illu- than one image of the same person,while Self Quotient mination changes,and "the variations between the im- Image and Eigenphases have comparatively high com- ages of the same face due to illumination are almost al- putational complexity.Histogram equalization and log- ways larger than image variations due to change in face arithm transforms are easy to implement and don t re- identity"[41.Fig.1 shows the same person under dif- quire other images,but their performance is not good ferent illumination conditions in Yale Face Database enough. Blsj A novel illumination preprocessing method for hu- man face recognition was proposed and is discussed in this paper.Two major advantages of the method are that it has a low computational complexity and requires Fig.1 The same person under different illumination condi- no other images. tions in Yale Face Database B The remainder of this paper is organized as fol- Many methods have been proposed to deal with lows.Section 1 introduces the human face model and the illumination problem,including illumination illumination model adopted in this paper.Section 2 de- Received Date: scribes the proposed method in detail.Sections 3 and 4 Corresponding Author: show the experimental results and conclusions