Sonar Image Processing Based on C-V Algorithm

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Abstract Target detection in sonar images is a key step in the process of underwater target recognition. Due to the influence of noise and environment, the contours of targets in sonar images often have large irregularities, the image resolution is low, and the details are relatively small, making it difficult to be accurate. An underwater target is detected. The C-V algorithm based on curve evolution theory and level set method can only use an initial closed curve to detect multiple areas with similar gray values in the sonar image and can also detect target areas with internal holes, without the need for detection. Experiments have proved that through the use of threshold filtering, morphological filtering, and C-V algorithm, the target contour can be successfully extracted from the original sonar image, which is beneficial to the subsequent target recognition based on a large amount of experimental data.KeywordsTarget detectionLevel set methodC-V algorithmSonar image processing