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Proceedings Paper

Complex spatial images for multiparameter distortion-invariant optical pattern recognition and high-level morphological transforms
Author(s): Michael E. Lhamon; Laurence G. Hassebrook; Jyoti P. Chatterjee
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Paper Abstract

Detection of distorted target images is a common problem in optical pattern recognition. Many distortion-invariant filter designs have been developed. However, while detecting the distorted target, the value of the distortion parameters is lost. We introduce a method of optical morphology that transforms rotated target objects into a single line of bright dots. The location of these lines indicates the location of a target and the angle indicates the rotation of the target. We use a set of complex filter images referred to as super images configured in a correlation filter bank to accomplish this form of morphological transformation. The mathematical characteristics of super images are discussed and examples of their usage are demonstrated numerically.

Paper Details

Date Published: 15 March 1996
PDF: 8 pages
Proc. SPIE 2752, Optical Pattern Recognition VII, (15 March 1996); doi: 10.1117/12.235657
Show Author Affiliations
Michael E. Lhamon, Univ. of Kentucky (United States)
Laurence G. Hassebrook, Univ. of Kentucky (United States)
Jyoti P. Chatterjee, Univ. of Kentucky (United States)


Published in SPIE Proceedings Vol. 2752:
Optical Pattern Recognition VII
David P. Casasent; Tien-Hsin Chao, Editor(s)

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