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Image registration is an essential step in many image processing applications that need visual information from multiple images for comparison, integration or analysis. Recently researchers have introduced image registration techniques using the log-polar transform (LPT) for its rotation and scale invariant properties. However, there are two major problems with the LPT based image registration method: inefficient sampling point distribution and high computational cost in the matching procedure. Motivated by the success of LPT based approach, we propose a novel pre-shifted logarithmic spiral (PSLS) approach that distributes the sampling point more efficiently, robust to translation, scale, and rotation. By pre-shifting the sampling point by π/n_θ radian, the total number of samples in the angular direction can be reduced by half. This yields great reduction in computational load in the matching process. Translation between the registered images is recovered with the new search scheme using Gabor feature extraction to accelerate the localization procedure. Experiments on real images demonstrate the effectiveness and robustness of the proposed approach for registering images that are subjected to scale, rotation and translation.