Abstract
One of the method that can be used in the process of coordinate transformation, where the coordinate of some points may be affected by gross errors, is a method called RANSAC (Random Sample and Consensus). The stage hypothesis of this method is related to the concept of the minimal sample set (MSS) which is also called a hypothetical model. First minimal sample set is randomly selected from the input dataset and the model parameters are computed using only the elements of the MSS. Next, in testing step, RANSAC iteratively checks which observations of the entire dataset are consistent with the hypothetical model. The authors presented the possibility of using the RANSAC method in the process of transformation parameters estimation with some modification. The authors propose the use of some functions during the selection the MSS from the input data set so that they were not chosen randomly.
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