Fast Segmentation Method for Sonar Images Blurred by Noise Reduction

Mao Hande; Zhipeng Xu; Sheng Chang; Yuliang Liu; Xiangcheng Zhu

doi:10.20944/preprints202010.0323.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Version 1 : Received: 14 October 2020 / Approved: 15 October 2020 / Online: 15 October 2020 (13:10:41 CEST)

It has remained a hard nut for years to segment sonar images, most of which are noisy images with inevitable blur after noise reduction. For the purpose of solutions to this problem, a fast segmentation algorithm is proposed on the basis of the gray value characteristics of sonar images. This algorithm is endowed with the advantage in no need of segmentation thresholds to be calculated. To realize this goal, it follows the undermentioned steps: first, calculate the gray matrix of the fuzzy image background. After adjusting the gray value, segment the region into the background region, buffer region and target regions. After filtering, reset the pixels with gray value lower than 255 to binarize images and eliminate most artifacts. Finally, remove the remaining noise from images by means of morphological image processing. The simulation results of several sonar images show that the algorithm can segment the fuzzy sonar image quickly and effectively, with no problem of incomplete image target shape. Thus, the stable and feasible method is testified.

Image segmentation; sonar image; ocean engineering；morphological image processing

ENGINEERING, Automotive Engineering

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Fast Segmentation Method for Sonar Images Blurred by Noise Reduction

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