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Infrared target detection based on local contrast method and LK optical flow
Pan, Jiajia1,2; Tian, Yan1; Zhang, Xing1,2; Hao, Wei1
2018-11-09
Conference Name3rd Optoelectronics Global Conference, OGC 2018
Source Publication2018 the 3rd Optoelectronics Global Conference, OGC 2018
Pages176-179
Conference Date2018-09-04
Conference PlaceShenzhen, China
PublisherInstitute of Electrical and Electronics Engineers Inc.
Contribution Rank1
Abstract

A robust and effective small dim object detection algorithm is the key to the success of an infrared tracking system. To help solve practical tracking problems, a detecting algorithm based on local contrast method (LCM) and Lucas-Kanade method (LK) is put forward. Firstly, the local contrast map of the input image is obtained using the local contrast measure which measures the dissimilarity between the current location and its neighborhoods. In this way, target signal enhancement and background clutter suppression are achieved simultaneously. Secondly, an adaptive threshold is applied to extract the suspected object regions. Finally, the central points of obtained regions are used as characteristic points, then LK optical flow algorithm to calculate optical flow at these points, and through the instantaneous velocity calculation and selection targets are detected. The experimental result shows that this method works perfectly and can effectively detect infrared targets under complex backgrounds. ? 2018 IEEE.

Department光电测量技术实验室
DOI10.1109/OGC.2018.8529967
Indexed ByEI
ISBN9781538673973
Language英语
EI Accession Number20185006248796
Citation statistics
Document Type会议论文
Identifierhttp://ir.opt.ac.cn/handle/181661/30865
Collection光电测量技术实验室
Affiliation1.Xi'An Institute of Optics and Precision Mechanics, Chinese Academy of Science, Xi'an, China;
2.University of Chinese Academy of Science, Beijing, China
Recommended Citation
GB/T 7714
Pan, Jiajia,Tian, Yan,Zhang, Xing,et al. Infrared target detection based on local contrast method and LK optical flow[C]:Institute of Electrical and Electronics Engineers Inc.,2018:176-179.
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