PPM Translation, Rotation and Scale in D-Dimensional Space by the Discrete to Continuous Approach

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Point pattern matching (PPM), is an important problem arises in many computer visions, pattern recognition and computational geometry fields. This paper presents an important amelioration and generalization of discrete to continuous approach. With a very fast running time, numerically stable, easy to implement and dealing with large PPM applications and fields in d-dimensional space. The power of this approach resides in the passage from the discrete to the continuous, considering the issue in its entity. The experimental results in 2D and 3D show that with these new amelioration, our approach becomes very efficient.