Inspection, Identification and Repair Monitoring of Cracked Concrete structure –An application of Image processing

The aim of this research is to identify the cracks on concrete walls and classify them into voids, cracks and micro thin cracks. It is imperative to plan an optimal repair technique that considers the necessary causes and problems that require special attention during repair. The proposed framework integrates Unmanned Aerial Vehicles (UAVs), data acquisition procedures and image processing for crack detection and evaluation of surface degradation. An ideal approach is implemented, Speeded Up Robust Features (SURF) and Scale-Invariant Feature Transform (SIFT) techniques are used for crack detection. The acquired images are section-overlapped and stitched together using image stitching program. In addition to the aforementioned strategies, gray-scale thresholding (where gray-scale is converted into binary) is a technique that is utilized for measurement of surface deterioration.