Sonar image target detection based on multi-region optimal selection strategy

Abstract

To overcome the adverse effects of noise and shadow regions on target detection in side-scan sonar images, more precisely, it is difficult to accurately detect targets, a target detection technology based on a multi-region optimal selection strategy of spectral clustering combined with the entropy weight method is proposed in this study. First, the cluster numbers for spectral clustering are set in advance based on prior knowledge, and the pixels of the sonar image are clustered into several different regions. Second, the invariable features of translation, rotation and scaling up that each region is extracted and used to construct the feature criterion matrix for the multiple regions. Last, the entropy weight method is used to calculate the weights of each feature and the comprehensive weighted score of each region for this feature criterion matrix to obtain the final target region. Experimental results show that the proposed method can effectively overcome the adverse effects of noise and shadow regions in side-scan sonar images, but also achieve the selection of optimal target region among multiple regions after image clustering, thus verifying the feasibility and effectiveness of the proposed method in this study.

Keywords

• 声呐图像
• 目标
• 图像分割
• 谱聚类
• 特征选择
• 熵权法