Determining optimally orthogonal discriminant vectors in DCT domain for multiscale-based face recognition

Yanmin Niu; Xuchu Wang

doi:10.1117/12.887600

4 February 2011 Determining optimally orthogonal discriminant vectors in DCT domain for multiscale-based face recognition

Yanmin Niu, Xuchu Wang

Author Affiliations +

Proceedings Volume 7752, PIAGENG 2010: Photonics and Imaging for Agricultural Engineering; 77521B (2011) https://doi.org/10.1117/12.887600
Event: International Conference on Photonics and Image in Agricultural Engineering (PIAGENG 2010), 2010, Qingdao, China

Abstract

This paper presents a new face recognition method that extracts multiple discriminant features based on multiscale image enhancement technique and kernel-based orthogonal feature extraction improvements with several interesting characteristics. First, it can extract more discriminative multiscale face feature than traditional pixel-based or Gabor-based feature. Second, it can effectively deal with the small sample size problem as well as feature correlation problem by using eigenvalue decomposition on scatter matrices. Finally, the extractor handles nonlinearity efficiently by using kernel trick. Multiple recognition experiments on open face data set with comparison to several related methods show the effectiveness and superiority of the proposed method.

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Yanmin Niu and Xuchu Wang "Determining optimally orthogonal discriminant vectors in DCT domain for multiscale-based face recognition", Proc. SPIE 7752, PIAGENG 2010: Photonics and Imaging for Agricultural Engineering, 77521B (4 February 2011); https://doi.org/10.1117/12.887600

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KEYWORDS

Feature extraction

Facial recognition systems

Image filtering

Antimony

Image compression

Databases

Image enhancement

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