A Template Matching Method for Multi-Scale and Rotated Images Using Ring Projection Vector Conversion

Abstract

Template matching is a process of finding template image location from a known image, which is one of the main research contents in machine vision. For the multi-scale and rotated image template matching, most of template matching algorithms usually form a templates collection with different scaling ratios templates, and then the templates in the collection are matched separately. The algorithm will greatly increase the calculation burden of template matching, and the matching efficiency will be greatly reduced. This paper proposes an algorithm for multi-scale and rotated image template matching. The algorithm first computes the ring projection vector of the template, and then, the ring projection of the scaled template can be obtained by ring projection vector conversion. The normalized cross correlation is used to calculate the similarity between the new ring projection vector and the ring projection vector of each point of the scene image. In the end the similarities determine the optimal matching position and scale ratio. Experimental results show that the proposed algorithm can accurately find the correct matching position for multi-scale and rotated image template matching.