A novel crack detection algorithm of underwater dam image

C. Chen, Jian Wang, Lei Zou, Jun Fu, Cong Ma
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引用次数: 14

Abstract

A novel algorithm is introduced for the deficiencies of underwater dam image crack detection. The algorithm makes use of the intensity values of 2D image to generate a 3D spatial surface, which is regarded as a concave-convex ground with “pits” and “ditches”. The “pits” represent the noise pixels and the “ditches” represent the crack pixels. The cracks that are difficult to describe in 2D image can be regarded well as ditches in the 3D spatial surface. Then by analyzing the characteristics of ditches space curvatures, the space detected method is used to get the ditches information, which is mapped to 2D surface as the crack. Because the detected result contains some noise and fake cracks, so BP neural network is adopted to identify crack object. As a result, the crack information is detected successfully.
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一种新的水下大坝图像裂缝检测算法
针对水下大坝图像裂缝检测的不足,提出了一种新的算法。该算法利用二维图像的强度值生成三维空间表面,将其视为具有“坑”和“沟”的凹凸地面。“坑”表示噪声像素,“沟”表示裂纹像素。在二维图像上难以描述的裂缝在三维空间表面上可以看作是沟渠。然后通过对沟槽空间曲率特征的分析,采用空间检测方法获取沟槽信息,并将其映射到二维表面作为裂缝;由于检测结果中含有一定的噪声和假裂纹,因此采用BP神经网络对裂纹目标进行识别。成功检测到裂纹信息。
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