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Plenary Lecture

Image Enhancement Methods for Improving the Performance of Conventional Face Recognition Systems

Professor Hector Perez-Meana
National Polytechnic Institute of Mexico
Mexico
E-mail: hmpm@prodigy.net.mx

Abstract: The performance of many biometric pattern recognition schemes strongly depends on the image quality used during the identification or recognition tasks.  Thus several algorithms have been proposed for image enhancement that can be used as a preprocessing stage of previously developed algorithms in order to improve its recognition performance.  Such enhancement methods can be classified in:  Methods that modify a pixel value independently of the values of its neighbors, methods based the retinex theory and methods that modify the image histogram.  The methods included in the first group such as the gamma piecewise correction modify the pixel value independently of its neighbors.  These methods have low computational complexity, although their performance is not always good enough.  The methods based on the retinex theory assume that the image cam be represented as the product of illumination and reflectance which are independently processes and then recombined to synthesize the enhanced image.  Finally the methods base on the histogram modification, modified the distribution of pixels value in such way that the distribution values processed image produced a higher quality image with better contrast.  Because the performance of a biometric pattern recognition system can be significantly improved if reasonable good quality the images can be used during the recognition task, several efficient algorithms hav been proposed during the last few years which improve the performance of the conventional methods.  In this talk, a review of the classical and recently image enhancement methods is presented together with an evaluation regarding the improvement of the recognition performance that can be obtained when each of them is used together with a conventional face recognition system.

Brief biography of the speaker: Hector Perez-Meana received his M.S: Degree on Electrical Engineering from the Electro-Communications University of Tokyo Japan in 1986 and his Ph. D. degree in Electrical Engineering from the Tokyo Institute of Technology, Tokyo, Japan, in 1989. From March 1989 to September 1991, he was a visiting researcher at Fujitsu Laboratories Ltd, Kawasaki, Japan. From September 1991 to February 1997 he was with the Electrical Engineering Department of the Metropolitan University of Mexico City where he was a Professor. In February 1997, he joined the Graduate Studies and Research Section of The Mechanical and Electrical Engineering School, Culhuacan Campus, of the National Polytechnic Institute of Mexico, where he is now The Dean. In 1991 he received the IEICE excellent Paper Award, and in 2000 the IPN Research Award and the IPN Research Diploma. In 1998 he was Co-Chair of the ISITA’98, and in 2009 he was General Chair of The IEEE Midwest Symposium on Circuit and Systems (MWSCAS). Prof. Perez-Meana has published more that 100 papers and two books. He also has directed 17 PhD theses and more than 35 Master theses. He is a Senior member of the IEEE, member of The IEICE, The Mexican Researcher System and The Mexican Academy of Science. His principal research interests are adaptive systems, image processing, pattern recognition watermarking and related fields.

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