The periodic hollowing inspection of the existing building exterior wall is crucial for public safety and building energy conservation. Due to its non-destructive and intuition advantage, the infrared thermal detection is proposed to be an ideal survey method. However, much manual participation is required to distinguish the hollowing flaw relying on empirical judgment, and a heavy burden comes up when large-area diagnosis required. In order to improve the efficiency of hollowing detection, this investigation developed the Canny algorithm to realize the automatic processing using the computer instead of manual judgment.

At first, reasonable pieces of setting advice were given to get more clear hollowing region contours with the final recognition outcome comparison of different processing methods for each step. Besides, it was found that the hollowing contour gradient values are lower and exist in a short interval, and the segmentation threshold value was critical in the Canny edge-detection algorithm, which highly restricted the speed of processing large amounts of infrared images. To improve the efficiency of thermal image recognition, a threshold selection method based on the local maximum inter-class variance algorithm was introduced into the Canny edge-detection algorithm. Compared with Sobel, Roberts, Prewitt, and LoG, the proposed algorithm presented a better performance in the identification of hollowing edge contour according to the verification based on three cases. It revealed that the improved Canny edge-detection algorithm was effective and efficient, which could not only eliminate the influence of subjective factors but also achieve full-automatic and batch processing.

对既有建筑外墙进行定期挖空检查，对公共安全和建筑节能至关重要。由于其无损和直观的优点，红外热探测被认为是一种理想的测量方法。然而，依靠经验判断来区分空心缺陷需要大量的人工参与，在需要大面积诊断时负担很重。为了提高空心检测的效率，本研究开发了Canny算法，实现了计算机自动处理，而不是人工判断。

首先给出合理的设置建议，以获得更清晰的镂空区域轮廓，并比较不同处理方法对每一步的最终识别结果。此外，发现空心轮廓梯度值较低且存在于较短的区间内，而分割阈值在Canny边缘检测算法中至关重要，极大地限制了处理大量红外图像的速度。为提高热图像识别效率，在Canny边缘检测算法中引入了基于局部最大类间方差算法的阈值选择方法。与 Sobel、Roberts、Prewitt 和 LoG 相比，通过三种情况的验证，提出的算法在挖空边缘轮廓的识别中表现出较好的性能。结果表明，改进后的Canny边缘检测算法是有效且高效的，不仅可以消除主观因素的影响，而且可以实现全自动和批处理。