Pose and Illumination in Face Recognition Using Enhanced Gabor LBP & PCA
Journal Title: International Journal of Modern Engineering Research (IJMER) - Year 2014, Vol 4, Issue 4
Abstract
This paper presents the face recognition based on Enhanced GABOR LBP and PCA. Some of the challenges in face recognition are occlusion, pose and illumination .In this paper, we are more focused on varying pose and illumination. We divided this algorithm into five stages. First stage finds the fiducial points on face using Gabor filter bank as this filter is well known for illumination compensation. Second stage applies the morphological techniques for reduce useless fiducial points. Third stage applies the LBP on reduced fiducial points with neighborhood pixel for improving the pose variation. Forth stage uses PCA to detect the best variance points which are necessary to characterize the training images. The last recognition stage includes finding the Euclidean norm of the feature weight vectors with the test weight vector. In this project, we used 20 images of 20 different persons from ORL database for training. For testing, we used images with varying illumination, pose and occluded images of the same training persons. Using this algorithm, testing results has shown significant improvement performance
Authors and Affiliations
Manit Kapoor1 , Sumit Kapoor2
Keywords
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- EP ID EP115896
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