Iterative infrared ship target segmentation based on multiple features

被引:73
作者
Liu, Zhaoying [1 ,3 ,4 ]
Zhou, Fugen [1 ,3 ]
Chen, Xiaowu [2 ]
Bai, Xiangzhi [1 ,2 ,3 ]
Sun, Changming [4 ]
机构
[1] Beihang Univ, Image Proc Ctr, Beijing 100191, Peoples R China
[2] Beihang Univ, State Key Lab Virtual Real Technol & Syst, Beijing 100191, Peoples R China
[3] Beihang Univ, Beijing Key Lab Digital Media, Beijing 100191, Peoples R China
[4] CSIRO Computat Informat, N Ryde, NSW 1670, Australia
基金
中国国家自然科学基金;
关键词
Infrared ship target; Iterative segmentation; Global background subtraction filter; Adaptive row mean subtraction filter; Shape feature; Target selection; ACTIVE CONTOURS; IMAGE;
D O I
10.1016/j.patcog.2014.03.005
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents an efficient method for ship target segmentation in infrared (IR) images. It consists of mainly two procedures: iterative image segmentation and ship target selection. First, based on the intensity distribution of an IR image, we design a global background subtraction filter (GBSF) to suppress the background, and an adaptive row mean subtraction filter (ARMSF) to enhance the target. After iteratively applying these two filters, we can obtain a proper threshold for image segmentation. Second, based on the geometric properties of the ship target, we construct four shape features and a selection criterion to identify the real target and remove the non-target regions. Experimental results demonstrate that the proposed method can effectively segment ship targets from different backgrounds in IR images. The advantage of the proposed method over the others in the previous literatures is validated in both visual and quantitative comparisons, especially for IR images with low contrast and uneven intensities. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:2839 / 2852
页数:14
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