ROBUST IMAGE-BASED CRACK DETECTION IN CONCRETE STRUCTURE USING MULTI-SCALE ENHANCEMENT AND VISUAL FEATURES

Crack detection is an important technique to evaluate the safety and predict the life of a concrete asset. In order to improve the robustness of the crack detection in complex background, a new crack detection framework based on multi-scale enhancement and visual features is developed. Firstly, to deal with the effect of low contrast, a multi-scale enhancement method using guided filter and gradient information is proposed. Then, the adaptive threshold algorithm is used to obtain the binary image. Finally, the combination of morphological processing and visual features are adopted to purify the cracks. The experimental results with different images of real concrete surface demonstrate the high robustness and validity of the developed technique, in which the average TPR can reach 94.22%.