Image recognition method of building wall cracks based on feature distribution

Abstract

In order to solve the building damage caused by cracks in the wall surface, based on feature distribution and SAR image segmentation technology, the cracks in the building wall were identified by extracting feature data images, de-noising and enhancing image edges, and segmenting target images. The validity and feasibility of the method are verified by the actual concrete wall image. The results show that the recognition accuracy of cracks in non-cracked walls is 100%, and that of longitudinal cracks is 78.2%. Compared with the color feature discrimination, this method has a good processing effect on the image, clear crack line, good coincidence degree with the original image, and crack width is close to the width of the original image. After processing the image with rough set, the recognition rate of the image is 98.1%, the false reject rate is 1.9%, the recognition time is 12 min, and the execution time of the algorithm is 126 s. After the processing of gray histogram, the feature distribution of image set has a certain distribution transfer, but the transfer effect is not particularly obvious. It can be found that this method has advantages of high recognition accuracy, short time, and practical application value, significantly enhancing pretreatment effect.