Fast stitching method for multi-view images of cupping spots

Abstract

Aiming at the problems of cupping machine camera with a small field of view, complete and high-definition cupping spot characteristics need to be monitored in real time, so as to effectively ensure that the cupping machine can accurately control the cupping time to avoid harm to the human body and extracting the complete back contour for automatic acupuncture point positioning, a fast stitching method for multi-view image of cupping spots is proposed. The present study uses linear transformation and Gaussian smoothing to preprocess the images to enhance image details, improve contrast, and reduce the influence of tank occlusion; Then, we combine the BRISK algorithm and the match factor to match the image and estimate the overlapping area through establishing a binary tree model so as to improve the efficiency of feature point detection and matching. Experimental results show that compared with the AutoStitch, the image stitched which is high definition has no obvious seams, ghosting, and distortion. What’s more, the algorithm in this paper is more efficient and the back contour is more complete. The algorithm in this paper has good real-time performance and the clarity of the cupping spots is high, which is conducive to the subsequent real-time detection of the cupping spots. At the same time, the back contour of the image stitched by the algorithm in this paper is complete, which is conducive to the subsequent automatic acupuncture point positioning.