Rotation invariant neural pattern recognition system which can estimate a rotation angle

This paper presents a rotation invariant neural pattern recognition system, which can recognize a rotated pattern and estimate a rotation angle. The system is very effective for a rotated coin recognition problem, but is poor compared with human performance. It is well known that human sometimes recognizes a rotated pattern by means of the mental rotation. Such a fact, however, has never been considered and used in neural pattern recognition systems, especially in rotation invariant systems. Therefore, we examine the principle of mental rotation and apply it to a rotation invariant pattern recognition system. The system with such a principle could recognize a rotated pattern and estimate a rotation angle. It is shown that the system is effective to recognize a rotated pattern from results of computer simulation for a coin recognition problem