Abstract
In this paper, we introduce an efficient feature extraction method for character recognition. The EA strategy is used to maximize the Fisher linear discriminant function (FLD) over a high order Pseudo-Zernike moment. The argument, which maximizes the FLD criteria, is selected as the proposed weight function. To evaluate the performance of the proposed feature, experimental studies are carried out on the historic Middle-Age Persian characters. The numerical results show 96.8% recognition rate on the selected database with the weighted Pseudo-Zernike feature (with order 10) and 65, 111,16 neurons for the input, hidden, and output layers while this amount for the original Pseudo-Zernike is 93%.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Cai, J., Liu, Z.: Integration of Structural and Statistical Information for Unconstrained Handwritten Numeral Recognition. IEEE Trans. on Pattern Analysis and Machine Intelligence 21(3) (1999)
Arica, N., Yarman-Vural, F.T.: An Overview of Character Recognition Focused on Off-Line Handwriting. IEEE Trans. on Sys., Man., and Cybernetics 31(2) (2001)
Casey, R.G., Lecolinet, E.: A Survey of Methods and Strategies in Character Segmentation. IEEE Trans. on Pattern Analysis and Machine Intelligence 18(7) (1996)
Baily, R.R., Srinath, M.: Orthogonal moment features for use with parametric and non-parametric classifiers. IEEE Trans. Pattern Analysis and Machine Intelligence 18(4), 389–398 (1996)
Belkasim, S.O., Shridhar, M., Ahmadi, M.: Pattern recognition with moment invariants, a comparative study and new results. Pattern Recognition 24(12), 1117–1138 (1991)
Haddadnia, J., Ahmadi, M., Faez, K.: An efficient feature extraction method with pseudo-Zernike moment in RBF neural network-based human face recognition system. EURASIP journal on applied signal processing 9, 890–901 (2003)
Feng, Y., Shi, P.: Face Detection Based on Kernel Fisher Discriminant Analysis. Automatic Face and Gesture Recognition, 381–384 (2004)
Alba, E., Tomassini, M.: Parallelism and Evolutionary Algorithms. IEEE Trans. on Evolutionary Computation 6(5) (2002)
Pahlavy Handwritten Documents. Asian Institute of Shiraz University (1972)
Jain, A.K., Mao, J., Mohiuddin, K.M.: Artificial neural networks. A tutorial. Computer 29(3), 31–44 (1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Alirezaee, S., Aghaeinia, H., Faez, K., Fard, A.S. (2005). An Efficient Feature Extraction Method for the Middle-Age Character Recognition. In: Huang, DS., Zhang, XP., Huang, GB. (eds) Advances in Intelligent Computing. ICIC 2005. Lecture Notes in Computer Science, vol 3645. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11538356_103
Download citation
DOI: https://doi.org/10.1007/11538356_103
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28227-3
Online ISBN: 978-3-540-31907-8
eBook Packages: Computer ScienceComputer Science (R0)