A fast template matching method based on improved ring projection transformation and local dynamic time warping

Abstract Aiming at the difficulty with which conventional template matching algorithms can simultaneously solve the problems of rotation, scaling, and illumination changes, this paper proposed a two-stage fast template matching method with lower complexity. In the first stage, according to the improved ring projection transformation feature vectors, that was, 1-D profiles, a local dynamic time warping algorithm was used to calculate the similarities and the scaling factors by locally aligning the 1-D profiles. In the second stage, the orientation codes method was applied to calculate the rotation angle based on the scaling factor. Compared with conventional template matching methods, the proposed algorithm does not need numerous template images with different scaling factors to enrich the template feature library. Only one template image is required to calculate the scaling factor and the rotation angle. Experimental results showed that by virtue of the proposed algorithm, a very attractive matching accuracy was obtained in the range of 0.8-1.2 scaling factor and arbitrary rotation angle, which was robust to noise and illumination changes.