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Proceedings Paper

Eigenface-based method for distortion-invariant human face recognition
Author(s): Haisong Liu; Minxian Wu; Guofan Jin; Qingsheng He; Yingbai Yan
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Paper Abstract

In this paper, the K-L expansion for feature extraction has been combined with an incoherent optical correlator, which was previously constructed for human face recognition. In this new approach, the eigenfaces are used as the image filters in the reference plane of the correlator. Since the face images can be approximated by different linear combinations of a relatively few eigenfaces, they can be efficiently distinguished from one another by a small set of the weight coefficients, which is derived by projecting the input image onto every eigenface. The optical correlator is used as the feature extractor and the optical correlation results between the input image and the eigenfaces are used as the features. As a result, the recognition features can be got at a relatively high speed. Because the face images in the training set are selected to representing some typical distortions, the system can deal with the distortions to a large extent.

Paper Details

Date Published: 18 October 1999
PDF: 8 pages
Proc. SPIE 3808, Applications of Digital Image Processing XXII, (18 October 1999); doi: 10.1117/12.365884
Show Author Affiliations
Haisong Liu, Tsinghua Univ. (United States)
Minxian Wu, Tsinghua Univ. (China)
Guofan Jin, Tsinghua Univ. (China)
Qingsheng He, Tsinghua Univ. (China)
Yingbai Yan, Tsinghua Univ. (China)

Published in SPIE Proceedings Vol. 3808:
Applications of Digital Image Processing XXII
Andrew G. Tescher, Editor(s)

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