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Abstract Template matching is one of the basic techniques in computer vision, where the algorithm should search for a template image to analyze. It is heavily used in signal. Image and video processing. A lot of applications are based on template matching in object detection. Superresolustion, image denoisingand image compression. In this thesis, the rotation, scale, brightness and contrast invaritant grayscale matching problem is considered. An algorithm is proposed that 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. The computational complexity of the proposed algorithm has been computed and compared with the complexity of other state-of-the-art methods to show its effectiveness. The proposed algorithm is compared with eight existing state-of-the-art techniques. |