Robust target recognition based on fractal analysis

Judy Chen; Andrew A. Kostrzewski; Dai Hyun Kim; Gajendra D. Savant; Jeongdal Kim; Anatoly A. Vasiliev

doi:10.1117/12.292738

24 October 1997 Robust target recognition based on fractal analysis

Judy Chen, Andrew A. Kostrzewski, Dai Hyun Kim, Gajendra D. Savant, Jeongdal Kim, Anatoly A. Vasiliev

Proceedings Volume 3159, Algorithms, Devices, and Systems for Optical Information Processing; (1997) https://doi.org/10.1117/12.292738
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

Abstract

Fractal image processing technology has been recognized as having great potential in automatic target recognition (ATR) and image compression. In this paper, Physical Optics Corporation demonstrates the feasibility of using a fractal image processing technique as a new and efficient approach for signature, pattern, and object recognition. Using optical Fourier transform and a ring-wedge detection technique, we generate and measure the power spectral density of an input scene. The log-log plot of the power spectral density vs. spatial frequency provides a very valuable signature for each input. Experimental results show that we can successfully discriminate man-made objects from natural objects in input scenes by analyzing signatures obtained this way.

Citation Download Citation

Judy Chen, Andrew A. Kostrzewski, Dai Hyun Kim, Gajendra D. Savant, Jeongdal Kim, and Anatoly A. Vasiliev "Robust target recognition based on fractal analysis", Proc. SPIE 3159, Algorithms, Devices, and Systems for Optical Information Processing, (24 October 1997); https://doi.org/10.1117/12.292738

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