Journal Title : International Journal of Modern Trends in Engineering and Science


Author’s Name : H Srivigneshwari | U Neeraja  unnamed

Volume 03 Issue 10 2016

ISSN no:  2348-3121

Page no: 81-84

Abstract – Face recognition under blur, illumination and pose is a difficult task in image processing. The existing method performs good under illumination and pose, but fail in case of blurring. So we propose a new method for blurred face recognition. First the structure and texture blur-invariant features are extracted and the complete description on blurred image is generated by fusing those features .LPQ is extracted  in a densely sampled way and to enhance its performance a vector of locally aggregated descriptors (VLAD) is employed for texture blur-invariant feature. The histogram of oriented gradient (HOG) is used for structure blur-invariant feature. Then the improved HOG is extracted and then fused with the original HOG by canonical correlation analysis (CCA). For handling pose and illumination variations, we follow MOBILAP algorithm. The expected results demonstrate our improvements and performance in blurred face recognition.   

Keywords— Face Recognition; Illumination; Invariant Texture; Non-Uniform Motion


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