一种基于RANSAC的柱面图像配准算法

A RANSAC-Based Cylindrical Image Registration Algorithm

提出了一种基于RANSAC的柱面图像配准算法.首先采用NCC算法对检测出来的Harris角点进行粗匹配,然后采用两次改进的RANSAC算法删除误配,提高正确匹配角点的数量,最后对仿射变换模型参数进行Levenberg-Marquardt非线性优化以进一步降低图像的配准误差.实验结果表明:通过一次改进RANSAC去错配后角点有效匹配率达到约99.2%,通过二次改进RANSAC去错配后角点有效匹配率达到约99.6%,与现有算法相比,在同等条件下获得了更高的匹配有效率.

A RANSAC-based cylindrical image registration algorithm was presented.First,the algorithm makes a coarse matching for the detected Harris corner points by using the NCC algorithm.Then,it reduces the false matched pairs by the two pass of improved RANSAC algorithm to increase the number of right matched pairs.At last,it optimizes the affine transformation model parameters by using Levenberg-Marquardt algorithm to lower the registration error.Experiments have shown that the right matched ratio of Harris corner reaches 99.2%after one time of improved RANSAC,and reaches 99.6%after two times of improved RANSAC.Compared with the existing methods,it has achieved higher right matched ratio under similar conditions.