FRoTeMa: Fast and Robust Template Matching

Abstract

Template matching is one of the most basic techniques in computer vision, where the algorithm should search for a template image T in an image to analyze I. This paper considers the rotation, scale, brightness and contrast invariant grayscale template matching problem. The proposed algorithm uses a sufficient condition for distinguishing between candidate matching positions and other positions that cannot provide a better degree of match with respect to the current best candidate. Such condition is used to significantly accelerate the search process by skipping unsuitable search locations without sacrificing exhaustive accuracy. Our proposed algorithm is compared with eight existing state-of-the-art techniques. Theoretical analysis and experiments on eight image datasets show that the proposed simple algorithm can maintain exhaustive accuracy while providing a significant speedup.