红外与毫米波学报2019，Vol.38Issue(1)：125-132,8.DOI:10.11972/j.issn.1001-9014.2019.01.019
基于多模态特征图融合的红外热图像目标区域提取算法
Infrared thermal image ROI extraction algorithm based on fusion of multi-modal feature maps
摘要
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 lowaccuracy, a ROI of infrared thermal image extraction algorithm based on fusion of multi-modal feature map is proposed. Multi-modal feature maps are constructed by contrast, entropy, and gradient features, and region filling is performed to achieve ROI extraction.Newalgorithm is applied to actual collected photovoltaic solar panel image. Simulation results showthat the proposed algorithm has high average precision ( 93. 0553％), high average recall ( 90. 2841％), F1 index and J index are better than Grab Cut, less artificial marks, etc.. It can be effectively used for ROI extraction of infrared thermal images.关键词
红外热图像/对比度/熵/梯度Key words
infrared thermal image/contrast/entropy/gradient分类
信息技术与安全科学引用本文复制引用
朱莉,张晶,傅应锴,沈惠,张守峰,洪向共..基于多模态特征图融合的红外热图像目标区域提取算法[J].红外与毫米波学报,2019,38(1):125-132,8.基金项目
国家自然科学基金资助项目(61463035) （61463035）
中国博士后科学基金资助项目(2016M592117) （2016M592117）
江西省科技厅科学基金资助面上项目(20161BAB202045) （20161BAB202045）
江西省博士后科研择优资助项目(2016KY01) （2016KY01）
江西省科技厅杰出青年基金项目(2018ACB21038) （2018ACB21038）
