SALIENCY-BASED AUTOMATIC TARGET DETECTION IN FORWARD LOOKING INFRARED IMAGES

被引：0
|
作者：
Li, Wei [1 ]
Pan, Chunhong [1 ]
Liu, Li-xiong [2 ]
机构：
[1] Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100864, Peoples R China
[2] Beijing Inst Technol, Sch Comp Sci & Technol, Beijing, Peoples R China
来源：
2009 16TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-6 | 2009年
关键词：
forward looking infrared; saliency map; region of interest; shape matching; RECOGNITION;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A saliency-based target detection method for forward looking infrared (FUR) image is proposed. Firstly saliency, map is computed using scale-space representation and separated into dark saliency map (DSM) and bright saliency map (BSM). Secondly dark and bright regions of interest (ROI) are detected by respective type of saliency map using marker-based maximally stable extremal regions (MSER) detection algorithm. Finally, shape matching algorithm is applied after grouping of the two types of ROI for object detection. Experimental results show that this work provides a promising way to solve the problems caused by salient dark parts of target.
引用
收藏
页码：957 / +
页数：2
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