Abstract
This paper introduces the Center for Pattern Recognition and Machine Intelligence (CENPARMI) Farsi dataset which can be used to measure the performance of handwritten recognition and word spotting systems. This dataset is unique in terms of its large number of gray and binary images (432,357 each) consisting of dates, words, isolated letters, isolated digits, numeral strings, special symbols, and documents. The data was collected from 400 native Farsi writers. The selection of Farsi words has been based on their high frequency in financial documents. The dataset is divided into grouped and ungrouped subsets which will give the user the flexibility of whether or not to use CENPARMI’s pre-divided dataset (60% of the images are used as the Training set, 20% of the images as the Validation set, and the rest as the Testing set). Finally, experiments have been conducted on the Farsi isolated digits with a recognition rate of 96.85%.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Alamri, H., Sadri, J., Nobile, N., Suen, C.Y.: A Novel Comprehensive Database for Arabic Off-Line Handwriting Recognition. In: Proceedings of 11th International Conference on Frontiers in Handwriting Recognition (ICFHR 11), Montreal, Canada, pp. 664–669 (2008)
Bidgoli, A.M., Sarhadi, M.: IAUT/PHCN: Islamic Azad University of Tehran/ Persian Handwritten City Names, A very large database of handwritten Persian word. In: Proceedings of 11th International Conference on Frontiers in Handwriting Recognition (ICFHR 11), Montreal, Canada, pp. 192–197 (2008)
Dong, J.X., Krzyzak, A., Suen, C.Y.: A fast SVM training algorithm. International Journal of Pattern Recognition and Artificial Intelligence 17(3), 367–384 (2003)
Khosravi, H., Kabir, E.: Introducing a very large dataset of handwritten Farsi digits and a study on their varieties. Pattern Recognition Letters 28(10), 1133–1141 (2007)
Liu, C.-L., Nakashima, K., Sako, H., Fujisawa, H.: Handwritten digit recognition: Investigation of normalization and feature extraction techniques. Pattern Recognition 37(2), 265–279 (2004)
Liu, C.-L., Suen, C.Y.: A new benchmark on the recognition of handwritten Bangla and Farsi numeral characters. In: Proceedings of 11th International Conference on Frontiers in Handwriting Recognition (ICFHR 11), Montreal, Canada, pp. 278–283 (2008)
Mozaffari, S., El Abed, H., Margner, V., Faez, K., Amirshahi, A.: IfN/Farsi-Database: A Database of Farsi Handwritten City Names. In: Proceedings of 11th International Conference on Frontiers in Handwriting Recognition (ICFHR 11), Montreal, Canada, pp. 397–402 (2008)
Mozaffari, S., Faez, K., Faraji, F., Ziaratban, M., Golzan, S.M.: A Comprehensive Isolated Farsi/Arabic Character Database for Handwritten OCR Research. In: Proceedings of IWFHR 2006, Paris, France, pp. 23–26 (2006)
Otsu, N.: A threshold selection method from gray-level histogram. IEEE Trans. System Man Cybernet. 9, 1569–1576 (1979)
Clawson, P., Rubin, M.: Eternal Iran, p. 6. Palgrave Macmillan Publishers, New York (2005)
Shi, M., Fujisawa, Y., Wakabayashi, T., Kimura, F.: Handwritten numeral recognition using gradient and curvature of gray scale image. Pattern Recognition 35(10), 2051–2059 (2002)
Solimanpour, F., Sadri, J., Suen, C.Y.: Standard Databases for Recognition of Handwritten Digits, Numerical Strings, Legal Amounts, Letters and Dates in Farsi Language. In: Proceedings of 10th International Workshop on Frontiers in Handwriting Recognition (IWFHR 10), La Baule, France, pp. 743–751 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Haghighi, P.J., Nobile, N., He, C.L., Suen, C.Y. (2009). A New Large-Scale Multi-purpose Handwritten Farsi Database. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2009. Lecture Notes in Computer Science, vol 5627. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02611-9_28
Download citation
DOI: https://doi.org/10.1007/978-3-642-02611-9_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02610-2
Online ISBN: 978-3-642-02611-9
eBook Packages: Computer ScienceComputer Science (R0)