Abstract: A crack detection algorithm for protective wall based on machine vision for a range of issues is presented in this paper, such as complex texture and low contrast in surface image of protective wall, unfixed image shooting angle and distance causing relative threshold to be unusable. Firstly, the algorithm enhances the crack contrast through a pixel complement algorithm. Then the distributions of phase angles and gray levels are used to improve Canny operator for restraining the interfering edge points in the image background. Secondly, some multiple relative thresholds to eliminate complicated noise are set up according to the characteristics of crack. Finally, by forecasting the growing trend of the crack, the crack region has been complemented. The experimental results show that the algorithm can preferably detect and identify the crack of protective wall, and also can be applied to the crack detection in the surface of the traditional architectures.

Key words: protective wall for piles, crack detection, machine vision, Canny operator, relative threshold

摘要： 针对桩护壁表面图像纹理复杂、裂缝对比度低，图像拍摄角度及距离不固定导致绝对阈值无法适用等问题，提出一种基于机器视觉的桩护壁裂缝检测方法。利用像素点互补算法增强图像裂缝的对比度，利用相位角及灰度分布改进Canny算子来抑制图像背景中干扰物的边缘点，并根据裂缝特性设置多个相对阈值过滤噪声，通过预测裂缝发展趋势对裂缝进行补全。实验结果表明，该方法能够较好地检测和标识桩护壁裂缝区域，并且对传统建筑表面的裂缝检测同样适用。

关键词: 桩护壁, 裂缝检测, 机器视觉, Canny算子, 相对阈值