Complex spatial images for multiparameter distortion-invariant optical pattern recognition and high-level morphological transforms

Michael E. Lhamon; Laurence G. Hassebrook; Jyoti P. Chatterjee

doi:10.1117/12.235657

15 March 1996 Complex spatial images for multiparameter distortion-invariant optical pattern recognition and high-level morphological transforms

Michael E. Lhamon, Laurence G. Hassebrook, Jyoti P. Chatterjee

Author Affiliations +

Proceedings Volume 2752, Optical Pattern Recognition VII; (1996) https://doi.org/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.

Citation Download Citation

Michael E. Lhamon, Laurence G. Hassebrook, and 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); https://doi.org/10.1117/12.235657

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