An Improved Image Pre-processing Method for Concrete Crack Detection

Structure health monitoring of concrete structures has gained more attention in the recent years due to advancement in the technology. Different methods like acoustic, ultrasonic and image processing based inspection methods have been deployed to carry out an assessment of concrete structure. In this paper, work has been carried out to monitor the health of laboratory scale concrete objects using vision-based inspection. The objective is to provide a modified image pre-processing algorithms for accurate concrete crack detection. Different image processing based algorithms reviewed from existing literature were implemented and tested to detect cracks on the surface of a 15 × 15 × 15 cm concrete cube. Due to random unevenness on the surface of concrete blocks, designing of an accurate and robust algorithm becomes difficult and challenging. Developed algorithm was applied to different images of concrete cubes. Receiver operating characteristics analysis and computation time analysis along with result images were discussed in the paper. In order to validate the applicability of developed algorithm, test results of crack detection on practical crack images are presented. Python was used to develop algorithm along with OpenCV library for image processing functions.