Image stitching method based on asphalt pavement potholes

Abstract

An asphalt road pothole image stitching algorithm is proposed to address the issues of low feature point matching accuracy, loss of pothole disease information, ghosting and deformation of the pothole when using traditional image stitching algorithms. The goal is to stitch the images captured by the pavement image acquisition equipment to form a complete asphalt pavement picture with the disease information of the pothole area intact. The stitched image's pixel point coordinates are transformed to the coordinates of the reference image using a single-strain matrix after first extracting the pit regions in the image and extracting feature points for these regions using the MSER-SIFT feature extraction algorithm. Next, the best matching point pairs are found using an improved random sampling consistency algorithm. Finally, a region-weighted averaging approach is utilized to merge the images. The experimental asphalt road images include pavement images with sufficient light during the day, pavement images with complete pothole disease information, pavement images with incomplete potholes, and pavement pothole images at night to test the effectiveness of pavement stitching under various conditions. The research results show that this splicing method not only improves the matching accuracy and speed of the traditional splicing algorithm, but also ensures the integrity and invariance of the pavement pothole information.