Concrete Crack Identification and Image Mosaic Based on Image Processing

Abstract

Crack assessment is an essential process in bridge detection. In general, most non-contact crack detection techniques are not suitable for widespread use. The reason for this is that they all need to position the ruler at the inspection site in advance or calibrate the camera unit pixel size at a certain distance in a very intricate process. However, the object distance method in this paper can complete the calculation using only the crack image and the working distance, which are provided by an acquisition system equipped with a camera and laser range finder. First, the object distance method and the scale method are compared by calculating the crack width, and the results show that the object distance method is the more accurate method. Then, a double edge pixel statistical method is proposed to calculate the crack length, which solves the problem of redundant and missing pixels. In addition, the conventional mosaic algorithm is improved to realize an image mosaic for the more efficient splicing of crack images. Finally, a series of laboratory tests were conducted to verify the proposed approach. The experiments showed that the precision of crack length extraction can reach 92%, and the improved algorithm stitching precision can reach 98%.