On the minimum number of templates required for shift, rotation and size invariant pattern recognition

摘要

Human observers are generally capable of recognizing patterns invariant to their orientation, position and size within an image. Though techniques are available for similar performance in computer visual systems, most suffer from lack of uniqueness or computational complexity. In this paper we introduce a new adaptive approach to invariant pattern recognition which overcomes both these problems. This technique is based upon the intrinsic invariance properties of the pattern and the recognition criterion. Our simulations demonstrate that the number of templates required to gain efficient pattern recognition is considerably lower than previously thought.