The multichannel integration active contour framework for crack detection

Abstract

Crack is one of the most important defects to evaluate the health of concrete buildings. Hence, accurate detection is of great significance for the infrastructure maintenance. In this article, an efficient multichannel active contour model for crack extraction is proposed, which integrates various features of the cracks. Firstly, the nonlocal means technique is adopted to eliminate the effects of noise while preserving the edge details. Then, the novel multichannel active contour model energy function is constructed, which considers three characteristics of the cracks: (a) the intensity features map, which is on the basis of the distinct intensity of the cracks; (b) the saliency feature map, which is obtained by the frequency-tuned salient region detection; and (c) the line-like feature map, which is enhanced by the multi-scale Hessian filtering. Also, the line-like feature map is binarized by a set of morphological operations and the Otsu thresholding to initialize the active contour. The proposed approach has been compared with the existing detection models on the public database and the real-world cracks. The experimental results show the effectiveness and efficiency of the proposed model.