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Proceedings Paper

Scale-invariant face recognition method using spectral features of log-polar image
Author(s): Kazuhiro Hotta; Takio Kurita; Taketoshi Mishima
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Paper Abstract

This paper presents scale invariant face detection and classification methods which use spectral features extracted from Log-Polar image. Scale changes of a face in an image are represented as shift along the vertical axis in Log-Polar image. In order to make them robust to the scale changes of faces, spectral features are extracted from the each row of the Log-Polar image. Autocorrelations, Fourier power spectrum, and PARCOR coefficients are used as spectral features. Then these features are combined with simple classification methods based on the Linear Discriminant Analysis to realize scale invariant face detection and classification. The effectiveness of the proposed face detection method is confirmed by the experiment using the face images which are captured under the different scales, backgrounds, illuminations, and dates. We have also performed the experiments to evaluate the proposed face classification method using 2800 face images with 7 scales under 2 different backgrounds.

Paper Details

Date Published: 18 October 1999
PDF: 11 pages
Proc. SPIE 3808, Applications of Digital Image Processing XXII, (18 October 1999); doi: 10.1117/12.365870
Show Author Affiliations
Kazuhiro Hotta, Saitama Univ. (Japan)
Takio Kurita, Electrotechnical Lab. (Japan)
Taketoshi Mishima, Saitama Univ. (Japan)

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

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