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Proceedings Paper

Improvised super-resolution algorithm for face recognition
Author(s): Pushpendre Rastogi; Madhav Singh Chauhan
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Paper 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.

Paper Details

Date Published: 30 October 2009
PDF: 10 pages
Proc. SPIE 7496, MIPPR 2009: Pattern Recognition and Computer Vision, 74960H (30 October 2009); doi: 10.1117/12.833706
Show Author Affiliations
Pushpendre Rastogi, IIT Delhi (India)
Madhav Singh Chauhan, IIT Delhi (India)


Published in SPIE Proceedings Vol. 7496:
MIPPR 2009: Pattern Recognition and Computer Vision
Mingyue Ding; Bir Bhanu; Friedrich M. Wahl; Jonathan Roberts, Editor(s)

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