一种改进的特征点匹配算法

特征点匹配是计算机视觉中的关键步骤,在很多领域中都有着的重要应用。通过对当前图像特征点匹配方法的研究,提取一种基于特征点的灰度量和几何特征量相结合的匹配方法。该方法首先用Harris算法提取特征点;然后用极线约束减少搜索范围;最后用特征点的灰度量实现特征点匹配。该方法利用极线约束,克服了用灰度量进行特征点匹配计算量大的缺点,提高了匹配速度。实验表明,是一种准确快速的特征点匹配方法。

An Improved Feature Points Matching Algorithm

Feature points matching is the key step in computer vision,which have important applications. Through research current methods of feature points maching,a maching method,which based on the gray value and the geometric characteristics of the point,is proposed in the paper.First,it using Harris operator extracts feature point.Second,it reduces the search area by using epipolar constraint.Last,it uses the gray value of the feature point to achive maching. This method overcome the shortcoming of a large quantit...