A geometric reasoning based algorithm for point pattern matching

Point pattern matching (PPM) is an important topic in computer vision and pattern recognition. It can be widely used in many areas such as image registration, object recognition, motion detection, target tracking, autonomous navigation, and pose estimation. This paper discusses the incomplete matching problem of two point sets under Euclidean transformation. According to geometric reasoning, some definitions for matching clique, support point pair, support index set, and support index matrix, etc. are given. Based on the properties and theorems of them, a novel reasoning algorithm is presented, which searches for the optimal solution from top to bottom and could find out as many consistent corresponding point pairs as possible. Theoretical analysis and experimental results show that the new algorithm is very effective, and could be, under some conditions, applied to the PPM problem under other kind of transformations.