Fusing Local Patterns Of Gabor Magnitue For Recognition System

A. Askarunisa, N. Ganesh, A. Athiraja, S.Vignesh Manickam

Abstract


Face recognition is a process of analyzing (or) comparing face with the previously stored face images. Training phase involves the collection of images and checking it for the presence of noise.  A testing phase is a selection of particular image and testing with predefined images and the result shows whether the person is authorized (or) not. Histogram equalization is a process of minimizing the contrast of the image and normalizing which smoothens the image pixels. A Gabor feature extraction is an orientation process which gets the image based on head position changes and it can seen through discrete fourier transform. Pixel selection is the process of selecting 8 neighbourhood pixels based on the center pixels, and it is represented on the blocks. Image is tested (or) compared with predefined images stored on the database and selects corresponding correct image. Compared with previous technique it provides better performance.


Keywords


histogram, face recognition, Gabor feature extraction.

References


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