基于红外图像处理技术的建筑外窗缺陷面积计算研究

将红外热成像与图像处理技术结合应用于建筑外窗缺陷的检测, 提出一种外窗缺陷检测和面积计算方法。通过外窗缺陷检测实验, 利用压差法进行外窗空气渗透检测, 求出渗透的缺陷面积。将红外热成像仪采集的外窗红外图像进行图像的预处理、外窗缺陷的检测以及检测后的面积计算, 并建立外窗缺陷红外图像检测模型。结果表明: 利用加权平均法进行灰度化处理, 中值滤波进行降噪处理、图像锐化和直方图均衡化进行图像增强处理, 处理效果明显, 可作为外窗红外图像的预处理方式； Roberts算法对预处理后外窗红外图像的检测与实验值差异最小, 检测信息更接近实际缺陷位置；将处理方法和检测模型与建筑整体气密性检测结合, 能够在现场对外窗气密性能等级进行初步判定。

Abstract

A method for defect detection and area calculation of exterior windows of buildings is proposed by combining infrared thermal imaging technology and image processing technology. Using equipment for detection of building exterior window defects, the differential-pressure method was utilized to detect the air penetration of an exterior window, and the defective area of the air penetration of this window was calculated. Infrared images of the exterior window of the building collected by an infrared thermal imager were subjected to image preprocessing, exterior window defect detection, and area calculation after inspection. Then, an infrared-image detection model of exterior window defects was established. The results show that preprocessing can make use of the weighted average method for grayscale processing, the median filter for noise reduction, image sharpening, and histogram equalization for image enhancement processing. The outcome of the aforementioned approaches is evident. The detection of the pretreatment infrared image, which is obtained using the Roberts algorithm, minimizes the difference between the test and experimental values. This makes the detection information closer to the actual position of the defect. A primary assessment of the airtightness performance level of exterior windows can be achieved by comparing the results provided by the proposed infrared image processing technology with airtightness on-site tests.

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张玲玲, 许廒, 张继冉, 任攀攀, 丁立斌, 魏代晓. 基于红外图像处理技术的建筑外窗缺陷面积计算研究[J]. 红外技术, 2022, 44(12): 1358. ZHANG Lingling, XU Ao, ZHANG Jiran, REN Panpan, DING Libin, WEI Daixiao. Research on Calculation of Defect Area of Building Exterior Windows Based on Infrared Image Processing Technology[J]. Infrared Technology, 2022, 44(12): 1358.

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