Improvised super-resolution algorithm for face recognition

Pushpendre Rastogi; Madhav Singh Chauhan

doi:10.1117/12.833706

30 October 2009 Improvised super-resolution algorithm for face recognition

Pushpendre Rastogi, Madhav Singh Chauhan

Proceedings Volume 7496, MIPPR 2009: Pattern Recognition and Computer Vision; 74960H (2009) https://doi.org/10.1117/12.833706
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

In spite of years of research there is tremendous scope for improvement in face recognition systems. There is continuing requirement for better face recognition systems with lesser computational complexity and higher accuracy. In this paper a new algorithm is proposed which addresses these requirements by integrating the computationally efficient technique of Fisher faces with Super-Resolution. The algorithm helps in identifying a person from sub-pixel shifted low resolution facial images of those people whose high resolution images are present in our library. The focus of this paper is only on face recognition and not on face detection and extraction. Extensive testing of the proposed algorithm was performed on images from the Essex university Faces94 database. In our test many parameters such as the number of low resolution input images and registration error etc. were varied and their effect on the accuracy (i.e. percentage of correct results) and throughput of the face recognition system was studied. It is shown that this method has high accuracy and low computational complexity and that it is robust to Gaussian blur, and salt and pepper noises due to camera and errors in image registration through experimental results performed on Faces94 database.

Citation Download Citation

Pushpendre Rastogi and Madhav Singh Chauhan "Improvised super-resolution algorithm for face recognition", Proc. SPIE 7496, MIPPR 2009: Pattern Recognition and Computer Vision, 74960H (30 October 2009); https://doi.org/10.1117/12.833706

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KEYWORDS

Facial recognition systems

Image resolution

Super resolution

Detection and tracking algorithms

Databases

Image registration

Principal component analysis

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