Active Handwritten Character Recognition using Genetic Programming
Inhaltsverzeichnis
Reference
Ankur Teredesai and J. Park and Venugopal Govindaraju: Active Handwritten Character Recognition using Genetic Programming. Proceedings of EuroGP'2001, LNCS, Vol. 2038, pp. 371-379, Springer-Verlag, 18-20 April 2001.
DOI
http://link.springer.com/chapter/10.1007/3-540-45355-5_30
Abstract
This paper is intended to demonstrate the effective use of genetic programming in handwritten character recognition. When the resources utilized by the classifier increase incrementally and depend on the complexity of classification task, we term such a classifier as active. The design and implementation of active classifiers based on genetic programming principles becomes very simple and efficient. Genetic Programming has helped optimize handwritten character recognition problem in terms of feature set selection. We propose an implementation with dynamism in pre-processing and classification of handwritten digit images. This paradigm will supplement existing methods by providing better performance in terms of accuracy and processing time per image for classification. Different levels of informative detail can be present in image data and our proposed paradigm helps highlight these information rich zones. We compare our performance with passive and active handwritten digit classification schemes that are based on other pattern recognition techniques.
Extended Abstract
Bibtex
Used References
R Duda and P Hart. Pattern Classificaiton and Scene analysis. Wiley International, 1973.
J Favata and G Srikantan. A multiple feature/resolution approach to handprinted digit and character recognition. International Journal of Imageing Systems and Technology, 7:304–311, 1996. http://dx.doi.org/10.1002/(SICI)1098-1098(199624)7:4%3C304::AID-IMA5%3E3.0.CO;2-C
A Frietas. A genetic programming framework for two data mining tasks: Classification and generalized rule induction. In Genetic Programming 1997: Proc. 2nd Annual Conference, pages 96–101, Stanford University, July 1997. Morgan Kaufmann.
K Kinnear Jr. Advances in Genetic Programming. The MIT Press, 1994.
J Koza. Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press, 1992.
J Koza, F Bennett, D Andre, and M Keane. Genetic Programming III. Morgan Kaufmann Publishers, 1999.
G Miller, P Todd, and S Hegde. Designing neural networks using genetic algorithms. In Proceedings of International Conference on Genetic Algorithms,, pages 379–384, 1989.
J Park and V Govindaraju. Active character recognition using a *-like algorithm. In Proceedings of Computer Vision and Pattern Recognition, 2000.
J Park, V Govindaraju, and S Srihari. Ocr in a hierarchical feature space. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(4):400–407, April 2000. http://dx.doi.org/10.1109/34.845383
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