On cepstrum approach to sequential image matching

Sequential image matching is a basic problem in image analysis and computer vision. Among the existing methods, there are intensity-based approaches and feature-based approaches, however, there are still some problems with the existing methods. It is hoped that the cepstrum method provides a robust and accurate way to match sequential images instead of correlation algorithms. In the present paper, the authors report their work on the cepstrum approach to the matching of sequential images. They show that cepstrum analysis provides a robust and fast method for sequential image matching, even if the input is raw images. It is also shown that the power cepstrum computation cost can be reduced by replacing the two-dimensional Fourier transform with two-dimensional Hartley transform. Cepstrum can also be obtained directly from the Hartley transformation. Experimental results are given to support the analysis