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Underwater Object Recognition Using Transformable Template Matching Based on Prior Knowledge
Zhu, Jianjiang1; Yu SQ(余思泉)2,3; Han Z(韩志)2; Tang YD(唐延东)2; Wu CD(吴成东)3
Department机器人学研究室
Source PublicationMATHEMATICAL PROBLEMS IN ENGINEERING
ISSN1024-123X
2019
Volume2019Pages:1-11
Indexed BySCI ; EI
EI Accession number20191006591361
WOS IDWOS:000459075500001
Contribution Rank2
Funding OrganizationNational Natural Science Foundation of China ; Youth Innovation Promotion Association CAS
AbstractUnderwater object recognition in sonar images, such as mine detection and wreckage detection of a submerged airplane, is a very challenging task. The main difficulties include but are not limited to object rotation, confusion from false targets and complex backgrounds, and extensibility of recognition ability on diverse types of objects. In this paper, we propose an underwater object detection and recognition method using a transformable template matching approach based on prior knowledge. Specifically, we first extract features and construct a template from sonar video sequences based on the analysis of acoustic shadows and highlight regions. Then, we identify the target region in the objective image by fast saliency detection techniques based on FFT, which can significantly improve efficiency by avoiding an exhaustive global search. After affine transformation of the template according to the orientation of the target, we extract normalized gradient features and calculate the similarity between the template and the target region, which can solve various difficulties mentioned above using only one template. Experimental results demonstrate that the proposed method can well recognize different underwater objects, such as mine-like objects and triangle-like objects and can satisfy the demands of real-time application.
Language英语
WOS SubjectEngineering, Multidisciplinary ; Mathematics, Interdisciplinary Applications
WOS KeywordSONAR IMAGE SEGMENTATION
WOS Research AreaEngineering ; Mathematics
Funding ProjectYouth Innovation Promotion Association CAS[2016183] ; National Natural Science Foundation of China[61303168] ; National Natural Science Foundation of China[61773367] ; National Natural Science Foundation of China[61773367] ; National Natural Science Foundation of China[61303168] ; Youth Innovation Promotion Association CAS[2016183]
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Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/24253
Collection机器人学研究室
Corresponding AuthorHan Z(韩志)
Affiliation1.School of Electrical & Automatic Engineering, Changshu Institute of Technology, Changshu 215500, China
2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
3.Faculty of Robot Science and Engineering, Northeastern University, Shenyang 110819, China
Recommended Citation
GB/T 7714
Zhu, Jianjiang,Yu SQ,Han Z,et al. Underwater Object Recognition Using Transformable Template Matching Based on Prior Knowledge[J]. MATHEMATICAL PROBLEMS IN ENGINEERING,2019,2019:1-11.
APA Zhu, Jianjiang,Yu SQ,Han Z,Tang YD,&Wu CD.(2019).Underwater Object Recognition Using Transformable Template Matching Based on Prior Knowledge.MATHEMATICAL PROBLEMS IN ENGINEERING,2019,1-11.
MLA Zhu, Jianjiang,et al."Underwater Object Recognition Using Transformable Template Matching Based on Prior Knowledge".MATHEMATICAL PROBLEMS IN ENGINEERING 2019(2019):1-11.
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