Extended target detection in complex background based on fractal theory

Kun-hua Zhang; Qi-heng Zhang; Xuan Yang

doi:10.1117/12.828757

20 May 2009 Extended target detection in complex background based on fractal theory

Kun-hua Zhang, Qi-heng Zhang, Xuan Yang

Proceedings Volume 7283, 4th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test and Measurement Technology and Equipment; 728331 (2009) https://doi.org/10.1117/12.828757
Event: AOMATT 2008 - 4th International Symposium on Advanced Optical Manufacturing, 2008, Chengdu, Chengdu, China

Abstract

The man-made target detection in natural background based on fractal theory has many advantages compared to traditional detection methods. While using single fractal feature to detect target, particularly extended target, is not robust in practice. Combing fractal feature with fractal scale invariance, a novel algorithm for extended target detection in complex background was proposed in this paper. First, through analyzing the self-similarity of fractal surface, the fractal feature named area measurement was developed to preliminary extract the target and the edges of image. According to the preliminary extraction result and the characteristic of extended target, potential target regions were detected. Then, the function of fractal area measurement changing with scale was proposed. Giving adaptive threshold, the backgrounds in potential target regions were eliminated by fractal scale invariance. Finally, the background conglutination was removed through mathematical morphology method if required. Experimental results demonstrate that the algorithm can detect extended target in complex background correctly and reliably, and the shape details of the target is reserved perfectly.

Citation Download Citation

Kun-hua Zhang, Qi-heng Zhang, and Xuan Yang "Extended target detection in complex background based on fractal theory", Proc. SPIE 7283, 4th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test and Measurement Technology and Equipment, 728331 (20 May 2009); https://doi.org/10.1117/12.828757

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KEYWORDS

Target detection

Fractal analysis

Detection and tracking algorithms

Mathematical morphology

Binary data

Algorithm development

Automatic target recognition

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