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  • Open Access


    Sonar Image Target Detection for Underwater Communication System Based on Deep Neural Network

    Lilan Zou1, Bo Liang1, Xu Cheng2, Shufa Li1,*, Cong Lin1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2641-2659, 2023, DOI:10.32604/cmes.2023.028037

    Abstract Target signal acquisition and detection based on sonar images is a challenging task due to the complex underwater environment. In order to solve the problem that some semantic information in sonar images is lost and model detection performance is degraded due to the complex imaging environment, we proposed a more effective and robust target detection framework based on deep learning, which can make full use of the acoustic shadow information in the forward-looking sonar images to assist underwater target detection. Firstly, the weighted box fusion method is adopted to generate a fusion box by weighted fusion of prediction boxes with… More > Graphic Abstract

    Sonar Image Target Detection for Underwater Communication System Based on Deep Neural Network

  • Open Access


    Fast Segmentation Method of Sonar Images for Jacket Installation Environment

    Hande Mao1,2, Hongzhe Yan1, Lei Lin1, Wentao Dong1,3, Yuhang Li1, Yuliang Liu2,4,*, Jing Xue5

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1671-1686, 2023, DOI:10.32604/iasc.2023.028819

    Abstract It has remained a hard nut for years to segment sonar images of jacket installation environment, 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 realize this goal, we follow the undermentioned steps: first, calculate the gray matrix of the fuzzy image background. After adjusting the gray value, the image is divided into three regions: background region, buffer… More >

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