Computer vision-based method for concrete crack detection

Abstract

This paper presents a computer vision-based method to automatically detect concrete cracks. We focus on images containing the concrete: background and crack, where the background is the major mode of the gray-scale histogram. Therefore, we address the detection problem of potential concrete cracks by dealing with histogram thresholding to extract regions of interests from the background. We first employ line emphasis and moving average filters to remove noise from concrete surface images obtained from an inspection robot. The developed algorithm is then applied for automatic detection of significant peaks from the gray-scale histogram of the smoothed image. The biggest peak and its corresponding valley(s) are consequently identified to calculate the threshold value for image binarization. The effectiveness of our proposed method was successfully evaluated on various test images, where cracks could be identified without the requirement of some heuristic reasoning.