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Fast infrared sea ship target detection based on improved BING algorithm
Li LX(李乐星); Shi ZL(史泽林); Liu YP(刘云鹏)
作者部门光电信息技术研究室
会议名称LIDAR IMAGING DETECTION AND TARGET RECOGNITION 2017
会议日期July 23-25, 2017
会议地点Changchun, China
会议主办者Chinese Society for Optical Engineering (CSOE)
会议录名称Proceedings SPIE 10605, LIDAR Imaging Detection and Target Recognition 2017
出版者SPIE
出版地Bellingham, USA
2017
页码1-6
收录类别EI ; CPCI(ISTP)
EI收录号20181705046878
WOS记录号WOS:000426279000059
产权排序1
ISSN号0277-786X
关键词Infrared Image Sea Ship Bing Algorithm Candidate Regions
摘要The key to the target detection of infrared sea ship is real-time, fast and efficient detection of the real goal. The BING method, which introduces the binarization approximation calculation, can quickly detect target. But for infrared images, the approximate calculation also brings some shortcomings. The approximation of the gradient feature makes the overall gradient of the image amplitude decrease and some of the smaller gradient edge details disappear, so that leading to the weak distinguished ability. Based on the BING algorithm, we propose an improved BING algorithm which can quickly extract the candidate regions of infrared ship images. In the normed gradients(NG) feature, we introduce the Laplace difference operator and use the two-level cascaded SVM to learn them. Experimental results have shown that our method is effective and rapid to extract the region of interest (ROI) of the target ship.
语种英语
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文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/21307
专题光电信息技术研究室
通讯作者Li LX(李乐星)
作者单位1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, P. R. China
2.College of Information Science and Engineering, Northeastern University, Shenyang, 110819, P. R. China
3.Key Laboratory of Opto-Electronic Information Processing, Chinese Academy of Sciences, Shenyang, 110016, P. R. China
4.The Key Lab of Image Understanding and Computer Vision, Shenyang, Liaoning province, 110016, P. R. China
推荐引用方式
GB/T 7714
Li LX,Shi ZL,Liu YP. Fast infrared sea ship target detection based on improved BING algorithm[C]//Chinese Society for Optical Engineering (CSOE). Bellingham, USA:SPIE,2017:1-6.
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