False match elimination for face recognition based on SIFT algorithm

Xuyuan Gu; Ping Shi; Meide Shao

doi:10.1117/12.896380

8 July 2011 False match elimination for face recognition based on SIFT algorithm

Xuyuan Gu, Ping Shi, Meide Shao

Proceedings Volume 8009, Third International Conference on Digital Image Processing (ICDIP 2011); 80092T (2011) https://doi.org/10.1117/12.896380
Event: 3rd International Conference on Digital Image Processing, 2011, Chengdu, China

Abstract

The SIFT (Scale Invariant Feature Transform) is a well known algorithm used to detect and describe local features in images. It is invariant to image scale, rotation and robust to the noise and illumination. In this paper, a novel method used for face recognition based on SIFT is proposed, which combines the optimization of SIFT, mutual matching and Progressive Sample Consensus (PROSAC) together and can eliminate the false matches of face recognition effectively. Experiments on ORL face database show that many false matches can be eliminated and better recognition rate is achieved.

Citation Download Citation

Xuyuan Gu, Ping Shi, and Meide Shao "False match elimination for face recognition based on SIFT algorithm", Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 80092T (8 July 2011); https://doi.org/10.1117/12.896380

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