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Proceedings Paper

Optical Gabor, wavelet, and morphological filters for image processing
Author(s): David P. Casasent; John Scott Smokelin; Anqi Ye
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Paper Abstract

We consider wavelet and Gabor transforms for detection of candidate regions of interest in a 2-D scene. We generate wavelet and Gabor coefficients for each spatial region of a scene using new linear combination optical filters to reduce the output dimensionality and to simplify post-processing. We use two sets of wavelet coefficients as indicators of edge activity to suppress background clutter. The Gabor coefficients are found to be excellent for object detection and robust to object distortions and contrast differences. We provide insight into the selection of the Gabor parameters.

Paper Details

Date Published: 12 January 1993
PDF: 11 pages
Proc. SPIE 1772, Optical Information Processing Systems and Architectures IV, (12 January 1993); doi: 10.1117/12.140911
Show Author Affiliations
David P. Casasent, Carnegie Mellon Univ. (United States)
John Scott Smokelin, Carnegie Mellon Univ. (United States)
Anqi Ye, Carnegie Mellon Univ. (United States)

Published in SPIE Proceedings Vol. 1772:
Optical Information Processing Systems and Architectures IV
Bahram Javidi, Editor(s)

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