The sequential similarity detection algorithm(SSDA) is studied to improve the conventional image matching,which is an efficient image matching algorithm.A threshold is given in the algorithm,which means the upper bound of distance between the template and the corresponding window in the image.A speed-up algorithm is proposed.The lower bound of distance between the template and the corresponding window is calculated and if the value exceeds the threshold,this window can be skipped.Experiments show that the proposed algorithm has a improvement in the speed compared to SSDA.

This paper presents a new fast template matching method with partial skipping using sub-template. In this method, we use sub-template to search point by point in the current searched window, and compare every SAD with threshold, if some SAD exceeds the threshold, set the new threshold equal to this SAD value and this point is one potential optimization location, when all points in the current window are compared, we will get a minimum value and a optimization location, then skip the other points whose SAD is not the minimum value. In other words, the searching step is that template size subtracts the subtemplate size, and we set the next threshold equal to the current optimization SAD value, we update the threshold and the optimal point until the end of the searched image like this, then will find the global minimum points and its SAD value. Experimental results show that the proposed method is near one hundred times faster than the conventional template match method.

Fast template matching with partial skipping using sub-template

A Speed-up Algorithm Based on SSDA

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A Speed-up Algorithm Based on SSDA

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Fast template matching with partial skipping using sub-template

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