Skip to main content
SpringerLink
Log in

Toward automatic development of handwritten personal Farsi/Arabic OpenType\(^{\textregistered }\) fonts

  • Original Paper
  • Published:
International Journal on Document Analysis and Recognition (IJDAR) Aims and scope Submit manuscript

Abstract

The interest in personalized handwritten fonts has been increased in recent years. This paper concerns with the automatic generation of Farsi/Arabic handwritten fonts. To reach this target, we need to extract the properties of the writer’s script style. The “glyphs” (simple characters or ligatures) of the writer’s script are extracted from the basic subwords. The basic subwords are acquired from a writer using tabular sheets. A learning method is used in extraction phase. After glyph extraction, four important steps are performed automatically: (a) adjusting glyphs joints and baselines (b) computing metric data, (c) locating dots, and (d) computing kerning pairs. Finally, the gathered information is compiled in an OpenType\(^{\textregistered }\) font file structure to generate a computer font, which can be used in any computer application. The results seem visually acceptable.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19

Similar content being viewed by others

References

  1. Awaida, S.M., Mahmoud, S.A.: State of the art in off-line writer identification of handwritten text and survey of writer identification of Arabic text. Educ. Res. Rev. 7(20), 445–463 (2012)

    Article  Google Scholar 

  2. Azmi, A., Alsaiari, A.: Arabic typography: a survey. Int. J. Electr. Comput. Sci. IJECS 9(10), 16–22 (2010)

    Google Scholar 

  3. Boeuf, S.: Arabic Font Production Tutorial. Khatt Books, Netherlands (2011)

    Google Scholar 

  4. Cano, J., Perez-Cortes, J., Arlandis, J., Llobet, R.: Training set expansion in handwritten character recognition. Structural, Syntactic, and Statistical Pattern Recognition, pp. 548–556. Springer, Berlin Heidelberg (2002)

    Chapter  Google Scholar 

  5. Chang, W., Shin, J.: A statistical handwriting model for style-preserving and variable character synthesis. Int. J. Doc. Anal. Recognit. 15(1), 1–19 (2012)

    Article  Google Scholar 

  6. Chen, Z., Zhou, B.: Effective radical segmentation of offline handwritten Chinese characters towards constructing personal handwritten fonts. In: Proc. of the 2012 ACM Symposium on Document Engineering, pp. 107–116. (2012)

  7. Cheng, W., Lopresti, D.: Parameter calibration for synthesizing realistic-looking variability in offline handwriting. In: Proc. of IS&T/SPIE Electronic Imaging, 78740Y, Document Recognition and Retrieval XVIII (2011)

  8. Elarian, Y.S., Al-Muhsateb, H.A., Ghouti, L.M.: Arabic handwriting synthesis. In: Proc. of the First International Workshop on Frontiers in Arabic Handwriting Recognition (2011)

  9. Fouladi, K., Araabi, B.N., Kabir, E.: A fast and accurate contour-based method for writer-dependent offline handwritten Farsi/Arabic subwords recognition. Int. J. Doc. Anal. Recognit. (IJDAR) 2(17), 181–203 (2014)

    Article  Google Scholar 

  10. Guyon, I.: Handwriting synthesis from handwritten glyphs. In: Proc. of the Fifth International Workshop on Frontiers of Handwriting Recognition, pp. 140–153. (1996)

  11. Haralambous, Y.: The traditional Arabic typecase extended to the unicode set of glyphs. Electron. Publ. 8(2 & 3), 111–124 (1995)

    Google Scholar 

  12. Haralambous, Y.: Fonts & Encodings. O’Reilly Media, Sebastopol (2007)

    Google Scholar 

  13. HighLogic Scanhand\(^{\textregistered }\). URL: http://www.high-logic.com/font-generator/scanahand.html. Retrieved: 3 Sep 2013

  14. Jou, F.D., Fan, K.C., Chang, Y.L.: Efficient matching of large-size histograms. Pattern Recognit. Lett. 25, 277–286 (2004)

    Article  Google Scholar 

  15. Kokula, M.: Automatic generation of script font ligatures based on curve smoothness optimization. Electron. Publ. 7(4), 217–229 (1994)

    Google Scholar 

  16. Kuroiwa, T., Shin, J.: Discovery of efficient Chinese characters for handwritten-style font generation. Int. J. Digit. Content Technol. Appl. (JDCTA) 5(12), 1–10 (2011)

    Article  Google Scholar 

  17. Liao, C., Huang, J.S.: Font generation by beta-spline curve. Comput. Graph. 15(4), 527–534 (1991)

    Article  MathSciNet  Google Scholar 

  18. Lin, Z., Wan, L.: Style-preserving English handwriting synthesis. Pattern Recognit. 40, 2097–2109 (2007)

    Article  Google Scholar 

  19. Liu, P., Xu, S., Lin, S.: Automatic generation of personalized Chinese handwriting characters. In: Proc. of the Fourth IEEE International Conference on Digital Home (ICDH), pp. 109–116. (2012)

  20. McQueen, C.D., Beausoleil, R.G.: Infinifont: a parametric font generation system. Electron. Publ. 6(3), 117–132 (1993)

    Google Scholar 

  21. Pal, S.K., Dutta, D.K.: Fuzzy Mathematical Approach to Pattern Recognition. Wiley Eastern Limited, New Delhi (1986)

    MATH  Google Scholar 

  22. Piška, K.: Fonts with complex OpenType tables. In: Proc. of Actes des conferences International ConTeXt Meeting & TeXperience (2010)

  23. Ristroph, J.H.: Multi-system font generation. Comput. Ind. Eng. 15(1), 467–474 (1988)

    Article  Google Scholar 

  24. Saabni, R.M., El-Sana, J. A.: Comprehensive synthetic Arabic database for on/off-line script recognition research. Int. J. Doc. Anal. Recognit. (IJDAR), 1–10 (2012)

  25. Sarfraz, M., Razzak, M.F.A.: An algorithm for automatic capturing of the font outlines. Comput. Graph. 26(5), 795–804 (2002)

    Article  Google Scholar 

  26. Sarfraz, M., Razzak, M.F.A.: A web based system to capture outlines of Arabic fonts. Inf. Sci. 150(3), 177–193 (2003)

    Article  Google Scholar 

  27. Sesa-Nogueras, E., Faundez-Zanuy, M.: Writer recognition enhancement by means of synthetically generated handwritten text. Eng. Appl. Artif. Intell. 26, 609–624 (2013)

    Article  Google Scholar 

  28. Shin, J., Suzuki, K.: Interactive system for handwritten-style font generation. In: Proc. of the Fourth IEEE International Conference on Computer and Information Technology (CIT’04), pp. 94–100. (2004)

  29. Srouji, J., Berry, D.M.: Arabic formatting with DITROFF/FFORTID. Electron. Publ. 5(4), 163–208 (1992)

    Google Scholar 

  30. Stanislav, K., Mestetskiy, L., Semenov, A.: Handwritten fonts modeling based on fat lines of variable width. In: Proc. of the 16th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision (WSCG’08), pp. 25–32. (2008)

  31. Suveeranont, R., Igarashi, T.: Example-based automatic font generation. Smart Graphics, pp. 127–138. Springer, Berlin Heidelberg (2010)

    Chapter  Google Scholar 

  32. Van Der Maaten, L., Postma, E.O.: Improving automatic writer identification. In: Proc. of the 17th Belgium-Netherlands Conference on Artificial Intelligence (BNAIC’05), pp. 260–266. (2005)

  33. Varga T., Bunke, H.: Generation of synthetic training data for an HMM-based handwriting recognition system. In: Proc. of the Seventh International Conference on Document Analysis and Recognition (ICDAR 2003), pp. 618–622. (2003)

  34. Vincent, N., Seropian, A., Stamon, G.: Synthesis for handwriting analysis. Pattern Recognit. Lett. 26(3), 267–275 (2005)

    Article  MATH  Google Scholar 

  35. Wada, A., Hagiwara, M.: Japanese font automatic creating system reflecting user’s Kansei. In: Proc. of IEEE International Conference on Systems, Man and Cybernetics, vol. 4, pp. 3804–3809. (2003)

  36. Wang, L., Lifeng, H.E., Nakamura, T., Mutoh, A., Itoh, H.: Calligraphy generation using deformable contours. IEICE Trans. Inf. Syst. 82(6), 1066–1073 (1999)

    Google Scholar 

  37. Williams, G.: Font creation with FontForge. In: Proc. of EuroTEX 2003, TUGboat, vol. 24(3), pp. 531–544. (2003)

  38. Williams, G.: Beyond glyphs, advanced typographic features of fonts. TeX, XML, and Digital Typography, pp. 257–263. Springer, Berlin Heidelberg (2004)

    Chapter  Google Scholar 

  39. Xiaohu, M., Zhigeng, P.: Automatic generation algorithm of high-quality outline font using Bezier curve. Zidonghua Xuebao/Acta Automatica Sinica 20(1), 121–125 (1994)

    Google Scholar 

  40. Xu, S., CM Lau, F., Cheung, W.K., Pan, Y.: Automatic generation of artistic Chinese calligraphy. IEEE Intell. Syst. 20(3), 32–39 (2005)

    Article  Google Scholar 

  41. Xu, S., Jin, T., Jiang, H., CM Lau, F.: Automatic generation of personal Chinese handwriting by capturing the characteristics of personal handwriting. In: Proc. of the 21st Innovative Applications of Artificial Intelligence Conference (IAAI’09), pp. 191–196. (2009)

  42. Yoshida, K., Nakagawa, Y., Köppen, M.: Interactive genetic algorithm for font generation system. In: IEEE World Automation Congress (WAC), pp. 1–6. (2010)

  43. Zhigeng, P., Xiaohu, M., Jiaoying, S.: The automatic generation algorithm for dynamic Chinese font. Zidonghua Xuebao/Acta Automation, Sinica 22, 591–596 (1996)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Control & Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran

    Kazim Fouladi & Babak N. Araabi

  2. School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran

    Kazim Fouladi & Babak N. Araabi

Authors
  1. Kazim Fouladi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Babak N. Araabi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Babak N. Araabi.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (pdf 116 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fouladi, K., Araabi, B.N. Toward automatic development of handwritten personal Farsi/Arabic OpenType\(^{\textregistered }\) fonts. IJDAR 18, 249–262 (2015). https://doi.org/10.1007/s10032-015-0241-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10032-015-0241-3

Keywords

Search

Navigation