15 March 1996 Complex spatial images for multiparameter distortion-invariant optical pattern recognition and high-level morphological transforms
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Proceedings Volume 2752, Optical Pattern Recognition VII; (1996); doi: 10.1117/12.235657
Event: Aerospace/Defense Sensing and Controls, 1996, Orlando, FL, United States
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.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael E. Lhamon, Laurence G. Hassebrook, Jyoti P. Chatterjee, "Complex spatial images for multiparameter distortion-invariant optical pattern recognition and high-level morphological transforms", Proc. SPIE 2752, Optical Pattern Recognition VII, (15 March 1996); doi: 10.1117/12.235657; https://doi.org/10.1117/12.235657
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KEYWORDS
Image filtering

Target detection

Transform theory

Optical pattern recognition

Distortion

Image processing

Image segmentation

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