DocumentCode :
437103
Title :
One efficient facet-based small target detection technique
Author :
Zheng, Sheng ; Xiong, Chengyi ; Tian, Jinwen ; Liu, Jim
Author_Institution :
Inst. for Pattern Recognition & Artificial Intelligence, Huazhong Univ. of Sci. & Technol., Wuhan, China
Volume :
1
fYear :
2004
fDate :
31 Aug.-4 Sept. 2004
Firstpage :
885
Abstract :
This paper presents a method for the detection of small objects from the infrared images. The detection is performed on the intensity surface well fitted by the cubic facet model. The small target energy distribution presents as a convex surface on the image intensity surface and the target center is the maximal extremum points of the convex surface. According to the extremum theory, the possible small target position is analytically determined by directly convolving the original image with the derivative operators deduced from the bivariate cubic function. With the available coarse target locations, the potential target is separated from the background by examining the intensity features of the target cluster. Experimental results on the sample infrared images demonstrate the proposed algorithm provides a robust and efficient performance.
Keywords :
image processing; infrared imaging; object detection; target tracking; bivariate cubic function; convex surface; cubic facet model; derivative operators; image intensity surface; infrared images; maximal extremum points; small target detection technique; Artificial intelligence; Face detection; Infrared detectors; Infrared imaging; Intelligent control; Maintenance; Object detection; Pattern recognition; Surface topography; Target tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on
Print_ISBN :
0-7803-8406-7
Type :
conf
DOI :
10.1109/ICOSP.2004.1452805
Filename :
1452805
Link To Document :
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