Image Matching Algorithm Based on Improved SSDA

摘要

In this paper, the classic template matching sequential similarity detection algorithm(SSDA) has a large amount of calculation and slow operation time, and an improved SSDA is proposed. By introducing the integral image, the point-by-point summation in the matching template window is transformed into the addition and subtraction of four positions in the integral image, which reduces the amount of calculation for point-by-point accumulation and summation. The laser image and the classic lena image are used as the experimental images to be matched, and the image with gray scale changes and noise added as the template image is used for image matching. Compared with the traditional normalized gray cross-correlation(NCC) algorithm and the improved NCC algorithm for integrating images, the experimental results show that the improved algorithm can shorten the running time, have a certain anti-interference ability against noise, and achieve image matching.