基于场强和凸壳的SIFT特征点匹配算法

传统尺度不变特征变换(SIFT)匹配算法的匹配结果易受参数影响。为此，提出一种于场强和凸壳的SIFT特征点匹配算法。在原始SIFT匹配方法基础上，结合特征点群的凸壳，引入引力场强概念刻画特征点群之间的空间特征关系，以进行图像点模式匹配，在匹配中充分利用特征点的几何空间信息。实验结果表明，该算法具有较高的匹配正确率，能找到更多的特征匹配点。

SIFT Feature Point Matching Algorithm Based on Field Intensity and Convex Hull

To overcome the defects that the traditional Scale Invariant Feature Transform(SIFT) method is sensitive to parameters applied, a SIFT feature point matching algorithm based on field intensity and convex hull is proposed. Based on the traditional SIFT matching method and the convex hull of the point sets in template and observe images, a concept of the gravitational field intensity in physics is introduced to depict the space relationships between features points for image matching in this paper. The proposed algorithm makes full use of the space geometry relationship between feature points in matching process. Experimental results show that, by using the proposed algorithm, the correct rate of matching between the point sets can be greatly improved, and can get more feature matching point.