基于p2-不变量的透视变换下的点模式匹配方法

点模式匹配是计算机视觉和模式识别领域中的一个重要问题 .通过研究 ,在假定待匹配的两个点模式中已知有三对点整体对应的前提下 ,基于射影坐标以及对投影变换和排序变换同时保持不变的 p2 -不变量等理论 ,通过定义一种广义距离 ,给出了一种求解透视变换下 ,点数不等的两个平面点模式匹配问题的新算法 .理论分析和仿真实验表明 ,该算法是快速、有效的

Point-Pattern Matching Under Perspective Transformation

Point pattern matching is an important problem in the fields of computer vision and pattern recognition. Its main task is to pair up the points in two images of a same scene when there is a geometric transformation relating the two images. Once the correspondences between the two sets of points are set up, we can recognize objects and locate their poses in many optical sensor applications. However it is well known that the imaging geometry of a TV camera is a nonlinear perspective transformation. To simplify the difficult solving process, many researchers approximate the perspective transformation relation with an affine transformation. Obviously it will increase the possibility of fault matchings. In this paper, a new algorithm is proposed to solve the problem of matching two point sets with the different cardinality under a perspective transformation without simplifying the original perspective transformation relation. Supposing two sets of three points have been matched as a whole beforehand, based on projective coordinates and p 2 invariant theory, a new concept named generalized distance is introduced. Theoretical analysis and simulation results show that the new algorithm is fast and effective.