基于分区自适应阈值的声呐障碍物检测算法研究

Research on Obstacle Detection Algorithm of Sonar Based on Partition Adaptive Threshold

摘要:

针对UUV避碰声呐探测障碍物过程中自主选择分割阈值进行障碍物检测的问题,提出了基于分区自适应阈值的障碍物检测算法。首先将避碰声呐图像均匀分为相同大小的图像块,对每个图像块基于最大类间方差算法确定该区域障碍物图像分割的高低阈值,然后对检测到的障碍物进行形态学处理去除孤立噪声点,对目标区域进行连通性分析及内部空洞处理,最终得到完整的障碍物轮廓信息。通过湖试数据验证表明了该方法对声呐障碍物检测的有效性。

Abstract:

An algorithm of obstacle detection based on partition adaptive threshold is proposed to solve the problem of UUVobstacle-avoidance sonar autonomously selecting segmentation threshold to detect obstacles. Firstly, the obstacle avoidance sonar im-age is evenly divided into image blocks with the same size, and the high and low thresholds values of obstacle image segmentation inthis area is determined based on Otsu for each image block. Then, the isolated noise points of detected obstacle are removed throughmorphological operation, and the connectivity analysis and hole treatment of the target area are carried out. Finally , the complete ob-stacle profile information is obtained. The data of lake trial has validated the effectiveness of this method for obstacle detection of sO-nar.