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Proceedings Paper

Image segmentation algorithm based on contourlet transform and background complexity
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Paper Abstract

In infrared image, the grey distribution of background and target are instability, so it has much difficulty in the target segmentation. In this paper, a novel image segmentation algorithm is presented which is based on Contourlet transform and background complexity. Firstly, using Contourlet transform, the structure information of target and background is obtained. Next, structure similarity of target and background is computed. Finally, through the structure similarity of target and background, segmentation threshold is adjusted adaptively. If the structure similarity of target and background is low, it indicates that background is simple, segmentation threshold is set with the grey information. If the structure similarity of target and background is high, segmentation threshold is set with the structure information. The simulation experiments show that the target can be segmented truly in the complex background environment. The algorithm not only reserves the advantage of the grey segmentation in simple background environment, but overcomes the limitation of the grey segmentation in complex background environment, shows better adaptability than the traditional image segmentation methods.

Paper Details

Date Published: 11 September 2013
PDF: 6 pages
Proc. SPIE 8907, International Symposium on Photoelectronic Detection and Imaging 2013: Infrared Imaging and Applications, 89072W (11 September 2013); doi: 10.1117/12.2033169
Show Author Affiliations
Xue Li, Luoyang Optoelectro Technology Development Ctr. (China)
Wei-hua Meng, Luoyang Optoelectro Technology Development Ctr. (China)
Aviation Key Lab. of Science and Technology on Airborne Guided Weapons (China)
Jingbo Xiang, Luoyang Optoelectro Technology Development Ctr. (China)
Aviation Key Lab. of Science and Technology on Airborne Guided Weapons (China)


Published in SPIE Proceedings Vol. 8907:
International Symposium on Photoelectronic Detection and Imaging 2013: Infrared Imaging and Applications
Haimei Gong; Zelin Shi; Qian Chen; Jin Lu, Editor(s)

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