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Proceedings Paper

In-class distortion tolerance, out-of-class discrimination, and clutter resistance of correlation filters that employ a space domain nonlinearity applied to wavelet-filtered input images
Author(s): Lamia S. Jamal-Aldin; Rupert C. D. Young; Christopher R. Chatwin
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Paper Abstract

A problem of central importance in pattern recognition is the generation of an invariant response to a set of in-class objects while simultaneously maintaining discrimination against set of out-of-class objects, often together with resistance to background clutter. We apply a non-linear pre- processing operation to a wavelet filtered input and reference image prior to a correlation operation, i.e. in the space domain rather than to the spectrum. The performance of the filter is investigated by simulation for several different bandpasses and different degrees of non-linearity. The modified wavelet filter shows superior performance to the linear filter in terms of tolerance to in-class variations, discrimination ability and, most particularly, in its robustness to clutter in the input scene. This new operation was also employed in the synthesis of a modified synthetic discriminant function (SDF) filter, by applying the non- linearity to each of the wavelet filtered training set images comprising the SDF. The filter shows good detectability of an object in clutter, excellent discrimination ability without the need to include the out of class objects in the SDF, and good invariance to out of plane rotation over a distortion range of up to 90 degrees. The processing sequence is suitable for implementation by a hybrid digital/optical arrangement in which the input image is wavelet filtered in real-time by a DSP and a bipolar amplitude spatial light modulator employed to introduce the pre-filtered image into an optical correlator.

Paper Details

Date Published: 23 March 1998
PDF: 12 pages
Proc. SPIE 3386, Optical Pattern Recognition IX, (23 March 1998); doi: 10.1117/12.304755
Show Author Affiliations
Lamia S. Jamal-Aldin, Univ. of Sussex (United Kingdom)
Rupert C. D. Young, Univ. of Sussex (United Kingdom)
Christopher R. Chatwin, Univ. of Sussex (United Kingdom)


Published in SPIE Proceedings Vol. 3386:
Optical Pattern Recognition IX
David P. Casasent; Tien-Hsin Chao, Editor(s)

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