Paper
18 October 1999 Eigenface-based method for distortion-invariant human face recognition
Haisong Liu, Minxian Wu, Guofan Jin, Qingsheng He, Yingbai Yan
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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.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Haisong Liu, Minxian Wu, Guofan Jin, Qingsheng He, and Yingbai Yan "Eigenface-based method for distortion-invariant human face recognition", Proc. SPIE 3808, Applications of Digital Image Processing XXII, (18 October 1999); https://doi.org/10.1117/12.365884
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KEYWORDS
Optical correlators

Feature extraction

Image filtering

Facial recognition systems

LCDs

Image processing

Computing systems

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