1.No.710 R&2.D Institute, CSSC
Sonar image segmentation plays a very significant role in the development of image segmentation technology. Due to the factors such as poor imaging quality, low resolution and unclear edge conditions of sonar images, it is difficult to screen and obtain large-scale target data sets, and the cost of manual annotation is high from time to time. The segmentation algorithm based on supervised segmentation method is often doing with high cost, including long test period, poor real-time performance, and high operation cost. In this paper, the unsupervised learning convolution neural network (UCNN) is introduced into the sonar image segmentation task. The segmentation model trains and tests by using one single frame sonar image, and finally obtains the sonar image after segmenting the shadow area and target highlight area through reasoning process. Through the analysis of the experimental results, it is proved that this method has good operation efficiency and accuracy, and has high real-time performance too.