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Underwater sonar image detection: A combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm
Wang, Xingmei1; Liu, Shu2; Liu, Zhipeng3
2017-05-18
发表期刊PLOS ONE
卷号12期号:5
文章类型Article
摘要This paper proposes a combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm to detect underwater objects in sonar images. Specifically, for the first time, the problem of inappropriate filtering degree parameter which commonly occurs in non-local spatial information and seriously affects the denoising performance in sonar images, was solved with the method utilizing a novel filtering degree parameter. Then, a quantum-inspired shuffled frog leaping algorithm based on new search mechanism (QSFLA-NSM) is proposed to precisely and quickly detect sonar images. Each frog individual is directly encoded by real numbers, which can greatly simplify the evolution process of the quantum-inspired shuffled frog leaping algorithm (QSFLA). Meanwhile, a fitness function combining intra-class difference with inter-class difference is adopted to evaluate frog positions more accurately. On this basis, recurring to an analysis of the quantum-behaved particle swarm optimization (QPSO) and the shuffled frog leaping algorithm (SFLA), a new search mechanism is developed to improve the searching ability and detection accuracy. At the same time, the time complexity is further reduced. Finally, the results of comparative experiments using the original sonar images, the UCI data sets and the benchmark functions demonstrate the effectiveness and adaptability of the proposed method.
WOS标题词Science & Technology
DOI10.1371/journal.pone.0177666
关键词[WOS]PARTICLE SWARM OPTIMIZATION ; CLUSTERING-ALGORITHM ; GENETIC ALGORITHM ; SEGMENTATION ; DISPATCH
收录类别SCI
语种英语
项目资助者National Natural Science Foundation of China(41306086) ; technology innovation talent special foundation of Harbin(2014RFQXJ105) ; Fundamental Research Funds for the Central Universities(HEUCF100606) ; China Scholarship Council (CSC)(201506685079)
WOS研究方向Science & Technology - Other Topics
WOS类目Multidisciplinary Sciences
WOS记录号WOS:000401672400065
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/15110
专题脑网络组研究中心
作者单位1.Harbin Engn Univ, Coll Comp Sci & Technol, Harbin, Heilongjiang, Peoples R China
2.Chinese Acad Sci, Inst Automat, Brainnetome Ctr, Beijing, Peoples R China
3.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc CAS, Beijing, Peoples R China
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GB/T 7714
Wang, Xingmei,Liu, Shu,Liu, Zhipeng. Underwater sonar image detection: A combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm[J]. PLOS ONE,2017,12(5).
APA Wang, Xingmei,Liu, Shu,&Liu, Zhipeng.(2017).Underwater sonar image detection: A combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm.PLOS ONE,12(5).
MLA Wang, Xingmei,et al."Underwater sonar image detection: A combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm".PLOS ONE 12.5(2017).
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