%0 Conference Paper %1 Fukumi1994 %A Fukumi, Minoru %A Omatu, Sigeru %A Nishikawa, Yoshikazu %B Proceedings of the IEEE International joint Conference on Neural Networks 1994, IJCNN'94 %D 1994 %I IEEE Computer Society %K angle coin estimation, extraction, feature invariant mental nets, neural pattern principle, recognition recognition, rotated rotation system %P 4390--4395 %R 10.1109/ICNN.1994.374975 %T Rotation invariant neural pattern recognition system which can estimate a rotation angle %U http://ieeexplore.ieee.org/iel2/3013/8562/00374975.pdf?tp=&arnumber=374975&isnumber=8562 %V 7 %X 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

@inproceedings{Fukumi1994, abstract = {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}, added-at = {2011-03-27T19:35:34.000+0200}, affiliation = {University of Tokushima, Faculty of Engineering, Department of Information Science and Intelligent Systems}, author = {Fukumi, Minoru and Omatu, Sigeru and Nishikawa, Yoshikazu}, biburl = {https://www.bibsonomy.org/bibtex/2d843b7006a86dada903f730002e94680/cocus}, booktitle = {Proceedings of the IEEE International joint Conference on Neural Networks 1994, IJCNN'94}, booktitleaddon = {27 Jun-2 Jul, 1994}, doi = {10.1109/ICNN.1994.374975}, file = {:./fukumi1994_00374975.pdf:PDF}, interhash = {91bad6b7ce906b1799cdcdd4141a015d}, intrahash = {d843b7006a86dada903f730002e94680}, keywords = {angle coin estimation, extraction, feature invariant mental nets, neural pattern principle, recognition recognition, rotated rotation system}, location = {#ieeeaddr#}, owner = {CK}, pages = {4390--4395}, publisher = {{IEEE} Computer Society}, timestamp = {2011-03-27T19:35:39.000+0200}, title = {Rotation invariant neural pattern recognition system which can estimate a rotation angle}, titleaddon = {\noop{}}, url = {http://ieeexplore.ieee.org/iel2/3013/8562/00374975.pdf?tp=&arnumber=374975&isnumber=8562}, urldate = {25-1-2008}, venue = {Orlando, Florida}, volume = 7, volumes = {7}, xcrossref = {CK:conf/ijcnn/1994}, year = 1994 }