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A detection and classification approach for underwater dam cracks

机译:水下大坝裂缝的检测与分类方法

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摘要

Underwater dam crack detection and classification based on visible images is a challenging task. The underwater environment is very complex with uneven illumination and serious noise problems, which often leads to the distortion of detection. In addition, there are few methods suitable for underwater dam crack classification. To solve these problems, a novel underwater dam crack detection and classification approach is proposed. Firstly, a dodging algorithm is used to eliminate the uneven illumination in the underwater visible images. Subsequently, a crack detection approach is proposed, where the local characteristics of image blocks and the global characteristics of connected domains are both used based on the analysis of the statistical properties of dam crack images. Finally, an improved evidence theory-based crack classification algorithm is proposed after the crack detection. Experimental results show that the proposed approach is able to detect underwater dam cracks and classify them accurately and effectively in complex underwater environments.
机译:基于可见图像的水下大坝裂缝检测和分类是一项艰巨的任务。水下环境非常复杂,照明不均匀且存在严重的噪声问题,这通常会导致检测失真。另外,很少有适合水下大坝裂缝分类的方法。为了解决这些问题,提出了一种新颖的水下大坝裂缝检测与分类方法。首先,使用躲避算法来消除水下可见图像中的不均匀照明。随后,提出了一种裂缝检测方法,该方法基于对大坝裂缝图像统计特性的分析,同时使用图像块的局部特征和连通域的整体特征。最后,提出了一种基于改进证据理论的裂纹检测算法。实验结果表明,该方法能够在复杂的水下环境中检测出水下大坝裂缝并将其准确有效地分类。

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