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

作　　者：WANG Xingmei LIU Shu LI Qiming LIU Zhipeng 

机构地区：[1]College of Computer Science and Technology, Harbin Engineering University [2]College of National Secrecy, Harbin Engineering University [3]Institute of Computing Technology, Chinese Academy of Sciences

出　　处：《Chinese Journal of Electronics》2018年第3期588-594,共7页电子学报（英文版）

基　　金：the National Natural Science Foundation of China(No.41306086)

摘　　要：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.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.

关 键 词：Quantum-inspired shuffled frog leaping algorithm（QSFLA） Underwater sonar image Fitness function Update strategy Fuzzy membership matrix 

分 类 号：TB56[交通运输工程—水声工程]