Underwater Sonar Image Detection: A Novel Quantum-Inspired Shuffled Frog Leaping Algorithm

WANG Xingmei; LIU Shu; LI Qiming; LIU Zhipeng

doi:10.1049/cje.2018.03.006

Volume 27 Issue 3

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WANG Xingmei, LIU Shu, LI Qiming, LIU Zhipeng. Underwater Sonar Image Detection: A Novel Quantum-Inspired Shuffled Frog Leaping Algorithm[J]. Chinese Journal of Electronics, 2018, 27(3): 588-594. doi: 10.1049/cje.2018.03.006

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WANG Xingmei, LIU Shu, LI Qiming, LIU Zhipeng. Underwater Sonar Image Detection: A Novel Quantum-Inspired Shuffled Frog Leaping Algorithm[J]. Chinese Journal of Electronics, 2018, 27(3): 588-594. doi: 10.1049/cje.2018.03.006

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Underwater Sonar Image Detection: A Novel Quantum-Inspired Shuffled Frog Leaping Algorithm

doi: 10.1049/cje.2018.03.006

1.
College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China;
2.
College of National Secrecy, Harbin Engineering University, Harbin 150001, China;
3.
Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China

Funds: This work is supported by the National Natural Science Foundation of China (No.41306086).

More Information

Corresponding author: LIU Shu (corresponding author) was born in 1994. He received the B.E. degree from Harbin Engineering University. He is now a master candidate of Institute of Automation, Chinese Academy of Sciences. His research interests include artificial intelligence and sonar image processing. (Email:2672644147@qq.com)
Received Date: 2017-10-27
Rev Recd Date: 2018-01-12
Publish Date: 2018-05-10

Abstract

Abstract

Object detection plays an important role in the underwater object recognition technology of sonar equipment. We propose a Novel quantum-inspired shuffled frog leaping algorithm (NQSFLA) to obtain more accurate detection results in this paper. The proposed NQSFLA adopts a fitness function combining intra-class difference with inter-class difference to evaluate the frog position more accurately and a new quantum evolution update strategy to improve the searching ability in the searching process. In order to avoid the disadvantages of Quantuminspired shuffled frog leaping algorithm (QSFLA), a fuzzy membership matrix with spatial information model is developed, which can remove isolated regions and further improve the detection accuracy. Segmentation, distribution and noise entropy (SDNE) model is also proposed to quantitatively evaluate the detection results. The detection results of the original sonar images demonstrate the effectiveness and adaptability of the proposed method.
- Quantum-inspired shuffled frog leaping algorithm (QSFLA),
- Underwater sonar image,
- Fitness function,
- Update strategy,
- Fuzzy membership matrix

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References

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