摘要
根据基本矩阵建立两幅图像间的极线约束关系,能有效减少误匹配。噪声干扰和对应点中的误匹配使得基本矩阵的解精度降低。介绍了极线几何和基本矩阵理论,在最小中值平方法的基础上,提出一种基于匹配点对之间协因数的RANSAC(random sampling consensus)算法估计基本矩阵,有效解决了因误匹配导致的基本矩阵估计结果恶化问题。实验结果表明,所提出算法能有效滤除误匹配,具有良好的鲁棒性。
The false match can be eliminated with epipolar constraint relation set up between two images based on the fundamental matrix.Noise disturbance and correspondence outliers made the precision of the fundamental matrix very low.This paper introduced the theory of epipolar geometry and fundamental matrix and put forward a RANSAC algorithm to estimate the fundamental matrix based on the least median square method,effectively solving the deterioration problem for the fundamental matrix estimation induced by the false match.Experimental results prove that the algorithm proposed in the paper can effectively eliminate the false matches and is of good robust nature.
出处
《山东科技大学学报（自然科学版）》
CAS
2011年第1期16-20,共5页
Journal of Shandong University of Science and Technology(Natural Science)
基金
国家自然科学基金项目(40871167)
国家西部1:5万地形图空白区测图工程项目(B2540)
关键词
图像匹配
基本矩阵
极线几何
最小中值平方法
image matching
fundamental matrix
epipolar geometry
least median square method
