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PLoS One. 2017 May 18;12(5):e0177666. doi: 10.1371/journal.pone.0177666. eCollection 2017.

Underwater sonar image detection: A combination of non-local spatial information and quantum-inspired shuffled frog leaping algorithm.

Author information

1
College of Computer Science and Technology, Harbin Engineering University, Harbin, Heilongjiang Province, P.R. China.
2
Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, PR China.
3
Key Lab of Intelligent Information Processing of CAS, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, PR China.

Abstract

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.

PMID:
28542266
PMCID:
PMC5436766
DOI:
10.1371/journal.pone.0177666
[Indexed for MEDLINE]
Free PMC Article

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