机械与电子2017，Vol.35Issue(7)：18-22,5.
结合改进粒子群算法的RANSAC精确匹配方法
On RANSAC Accurate Matching Method Based on Improved Particle Swarm Optimization Algorithm
吕铁钢 1张亚 1李世中1
作者信息
- 1. 中北大学机电工程学院,山西 太原 030051
- 折叠
摘要
Abstract
A RANSAC accurate matching method based on improved particle swarm optimization algorithm is presented in this paper to solve the problems of large calculation amount and low efficiency of accurate match in traditional random sampling consistency algorithm.Firstly,divide images into several parts by using the unit decomposition method in the differential manifold.Secondly,estimate and calculate the model parameters by using the improved particle swarm optimization algorithm to select the best leaf node.Finally,return to the optimal model with the N best leaf nodes kept,and calculate the accurate matching points in the different parts.By comparing the simulation experiment and the traditional RANSAC and GASAC,it finds out that the RANSAC accurate match method based on the improved particle swarm optimization algorithm has greatly improved the matching accuracy and the results stability,and reduced the number of false matching points.关键词
粒子群算法/RANSAC/单位分解/精确匹配Key words
particle swarm optimization/RANSAC/unit decomposition/accurate match分类
信息技术与安全科学引用本文复制引用
吕铁钢,张亚,李世中..结合改进粒子群算法的RANSAC精确匹配方法[J].机械与电子,2017,35(7):18-22,5.
