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A New Large-Scale Multi-purpose Handwritten Farsi Database

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Image Analysis and Recognition (ICIAR 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5627))

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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%.

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Author information

Authors and Affiliations

  1. CENPARMI (Centre for Pattern Recognition and Machine Intelligence) Computer Science and Software Engineering Department, Concordia University, Montreal, Quebec, Canada

    Puntis Jifroodian Haghighi, Nicola Nobile, Chun Lei He & Ching Y. Suen

Authors
  1. Puntis Jifroodian Haghighi
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  2. Nicola Nobile
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  3. Chun Lei He
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  4. Ching Y. Suen
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Waterloo, N2L 3G1, Waterloo, Ontario, Canada

    Mohamed Kamel

  2. Faculty of Engineering, Institute of Biomedical Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465, Porto, Portugal

    Aurélio Campilho

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© 2009 Springer-Verlag Berlin Heidelberg

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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

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  • 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)

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