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Optical Engineering

Automatic extraction of infrared small target based on support vector regression and adaptive region growing algorithm
Author(s): Ruiming Liu; Lei Yang; Erqi Liu; Jie Yang; Ming Li; Fanglin Wang
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Paper Abstract

A region-growing algorithm requires knowledge of the position of seed points in advance and must prespecify a threshold for the homogeneity test. Thus, the process of image segmentation by this algorithm cannot be implemented automatically, which often restricts its application in engineering practice. We propose an adaptive region-growing algorithm for automatically extracting small targets from an IR image. Using support vector regression (SVR), seed points can be detected automatically by regarding the intensity of an image as a surface. Furthermore, an adaptive threshold function is given as the criterion of the homogeneity test instead of a fixed threshold, as used in conventional region-growing algorithms. Our technique can extract small targets without human intervention. We carefully design many experiments to demonstrate its validity in extracting IR small targets.

Paper Details

Date Published: 1 April 2007
PDF: 5 pages
Opt. Eng. 46(4) 046402 doi: 10.1117/1.2724874
Published in: Optical Engineering Volume 46, Issue 4
Show Author Affiliations
Ruiming Liu, Shanghai Jiao Tong Univ. (China)
Lei Yang, Shanghai Jiao Tong Univ. (China)
Erqi Liu, China Aerospace Science & Industry Corp. (China)
Jie Yang, Shanghai Jiao Tong Univ. (China)
Ming Li, Shanghai Jiao Tong Univ. (China)
Fanglin Wang, Shanghai Jiao Tong Univ. (China)

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