PCB Image Registration Based on Improved SURF Algorithm
Xinyang Li, Hua He, Chuyun Huang, Yijian Shi · 2022 International Conference on Image Processing, Computer Vision and Machine Learning (ICICML) · 2022
In order to solve the problems of time-consuming and low matching accuracy in PCB image registration process, an improved speeded-up robust features (SURF) algorithm is proposed in this paper. The Shi-Tomasi algorithm was used to replace the SURF algorithm in order to extract the feature points in image overlapping area, and the feature points are described using the SURF descriptor. After matching, the progressive sampling consensus (PROSAC) algorithm was used to replace the random sample consensus (RANSAC) algorithm to refine the matched point pairs. The experimental results show that the total time of image registration is reduced by 34% compared with the traditional SURF algorithm, and the registration efficiency is significantly improved.