The battleplane target detection based on sky background

被引:0
作者
Liu Feng [1 ]
Liu Jun [1 ]
Wei XuGuang [2 ]
机构
[1] Hangzhou Dianzi Univ, Commun Informat Transmiss & Fus Technol Key Disci, Hangzhou 310018, Zhejiang, Peoples R China
[2] Northeastern Univ, Engn & Res Inst Co Ltd, Guiyang 550000, Peoples R China
来源
PROCEEDINGS OF THE 28TH CHINESE CONTROL AND DECISION CONFERENCE (2016 CCDC) | 2016年
关键词
Target detection; Image preprocessing; Image enhancement; Graph cut;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Battleplane is a kind of important strategic target in the military field, the research of using the infrared electric equipment to detect battleplane target is a hotspot in today's world. In view of this research background, we propose a method of battleplane target detection based on sky background. First, the infrared image of battleplane is preprocessed and collected by infrared electric equipment, and then we use the image enhancement technology on the preprocessed image according to the multi-scale fractal feature MFFK. Finally, we propose a method of graph cut segmentation to segment the enhanced image and the combination of prior knowledge to achieve battleplane target detection. The experimental results verify the effectiveness of the detection method, improve the real-time performance and the applicability of battleplane target detection.
引用
收藏
页码:5097 / 5101
页数:5
相关论文
共 8 条
[1]  
[郭宝龙 Guo Baolong], 2011, [模式识别与人工智能, Pattern Recognition and Artificial Intelligence], V24, P604
[2]  
Han Shou-Dong, 2011, Acta Automatica Sinica, V37, P11, DOI 10.3724/SP.J.1004.2011.00011
[3]  
Hu bureau new, 2014, NANJING NORMAL U J E, V04, P62
[4]  
Liu Jun, 2008, RES TARGET DETECTION
[5]  
Luo Qian, 2013, SKY BACKGROUND INFRA
[6]  
[汪国有 WANG Gouyou], 2006, [红外技术, Infrared Technology], V28, P287
[7]  
Xin Yunhong, 2014, J PHOTONICS, V02, P154
[8]   Topology cuts: A novel min-cut/max-flow algorithm for topology preserving segmentation in N-D images [J].
Zeng, Yun ;
Samaras, Dimitris ;
Chen, Wei ;
Peng, Qunsheng .
COMPUTER VISION AND IMAGE UNDERSTANDING, 2008, 112 (01) :81-90