Infrared thermal image ROI extraction algorithm based on fusion of multi-modal feature maps
Received:April 03, 2018  Revised:May 08, 2018  download
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Author NameAffiliationE-mail
ZHU Li Nanchang University lizhu@ncu.edu.cn 
ZHANG Jing Nanchang University 416114417181@email.ncu.edu.cn 
FU Ying-Kai Nanchang University 6130116028@email.ncu.edu.cn 
SHEN Hui Nanchang University huishen@email.ncu.edu.cn 
ZHANG Shou-Feng Nanchang University 416114417186@email.ncu.edu.cn 
HONG Xiang-Gong Nanchang University lizhu@ncu.edu.cn 
Abstract:Infrared thermal image region of interest(ROI) extraction has important significance for fault detection, target tracking and so on. In order to solve the problems of many infrared thermal image disturbances, artificial markers and low accuracy, a ROI of infrared thermal image extraction algorithm based on fusion of multi-modal feature map was proposed. Multi-modal feature maps were constructed by contrast, entropy, and gradient features, and region filling was performed to achieve ROI extraction. Apply the new algorithm to the actual collected photovoltaic solar panel image. The results show that the new algorithm has the advantages of high average precision (93.0553%), high average recall (90.2841%), F index and J index are better than Grab Cut, less artificial marks, etc.. It can be effectively used for ROI extraction of actual infrared thermal images.
keywords:infrared thermal image, contrast, entropy, gradient
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Copyright:《Journal of Infrared And Millimeter Waves》