Underwater sonar image detection: A combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm
文献类型：期刊论文
| 作者 | Wang, Xingmei1; Liu, Shu2; Liu, Zhipeng3 |
| 刊名 | PLOS ONE
 |
| 出版日期 | 2017-05-18 |
| 卷号 | 12期号:5 |
| DOI | 10.1371/journal.pone.0177666 |
| 文献子类 | Article |
| 英文摘要 | 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关键词 | PARTICLE SWARM OPTIMIZATION ; CLUSTERING-ALGORITHM ; GENETIC ALGORITHM ; SEGMENTATION ; DISPATCH |
| WOS研究方向 | Science & Technology - Other Topics |
| 语种 | 英语 |
| WOS记录号 | WOS:000401672400065 |
| 资助机构 | 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) |
| 源URL | [http://ir.ia.ac.cn/handle/173211/15110]  |
| 专题 | 自动化研究所_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 |
| 推荐引用方式 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). |
入库方式： OAI收割
来源：自动化研究所
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