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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
Source PublicationPLOS ONE
2017-05-18
Volume12Issue:5
SubtypeArticle
AbstractThis 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 HeadingsScience & Technology
DOI10.1371/journal.pone.0177666
WOS KeywordPARTICLE SWARM OPTIMIZATION ; CLUSTERING-ALGORITHM ; GENETIC ALGORITHM ; SEGMENTATION ; DISPATCH
Indexed BySCI
Language英语
Funding OrganizationNational 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 Research AreaScience & Technology - Other Topics
WOS SubjectMultidisciplinary Sciences
WOS IDWOS:000401672400065
Citation statistics
Cited Times:3[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/15110
Collection脑网络组研究中心
Affiliation1.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
Recommended Citation
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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