Point Pattern Feature Matching Method Based on Polar Coordinate

Infrared label point feature matching is one of the basic problems in the application direction of computer vision, pattern recognition and robot navigation and positioning. First, the center of the label point set and the weighted distance center are obtained in Cartesian coordinates, then the Cartesian coordinates are converted into polar coordinates to construct the position information feature vector of the label point set. Finally, using the method of spatial geometric constraints to compare each point in the label code to the feature vector, the matching result of the label code point set is obtained. The contributions of this paper are as follows: 1. A feature vector of label point set based on polar coordinate transformation is constructed, which makes the feature vector invariant to rotation, translation and illumination. 2. Using the combination of feature vector and spatial geometric constraints to screen label point pairs can effectively overcome the adverse effects of outlier points and noise. The final experiments demonstrate the effectiveness and robustness of the polar coordinate feature matching of label codes.