Skip to main content
SpringerLink
Log in

Feature combination for binary pattern classification

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

Abstract

The paper presents a novel framework for large class, binary pattern classification problem by learning-based combination of multiple features. In particular, class of binary patterns including characters/primitives and symbols has been considered in the scope of this work. We demonstrate novel binary multiple kernel learning-based classification architecture for applications including such problems for fast and efficient performance. The character/primitive classification problem primarily concentrates on Gujarati and Bangla character recognition from the analytical and experimental context. A novel feature representation scheme for symbols images is introduced containing the necessary elastic and non-elastic deformation invariance properties. The experimental efficacy of proposed framework for symbol classification has been demonstrated on two public data sets.

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.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

Notes

  1. Two conjuncts /ksha/ and /jya/ are also treated as basic consonant.

References

  1. Abbasi, S., Mokhtarian, F., Kittler, J.: Curvature scale space image in shape similarity retrieval. Multimed. Syst. 7, 467–476 (1999)

    Article  Google Scholar 

  2. Alajlan, N., El Rube, I., Kamel, M.S., Freeman, G.: Shape retrieval using triangle-area representation and dynamic space warping. Pattern Recognit. 40, 1911–1920 (2007)

    Article  MATH  Google Scholar 

  3. Antani, S., Agnihotri, L.: Gujarati character recognition. In: The Proceedings of International Conference on Document Analysis and Recognition, pp. 418–421 (1999)

  4. Atrey, PK., Hossain, MA., El Saddik, A., Kankanhalli, MS.: Multimodal fusion for multimedia analysis: a survey. Multimed Syst 16, 345–379 (2010)

  5. Barrat, S., Tabbone, S.: A Bayesian network for combining descriptors: application to symbol recognition. Int. J. Doc. Anal. Recognit. 13(1), 65–75 (2010)

    Article  Google Scholar 

  6. Belongie, S., Malik, J., Puzicha, J.: Shape matching and object recognition using shape contexts. IEEE Trans. Pattern Anal. Mach. Intell. 24(4), 509–522 (2002)

    Article  Google Scholar 

  7. Bicego, M., Murino, V., Figueiredo, M.A.: Similarity-based classification of sequences using hidden Markov models. Pattern Recognit. 37(12), 2281–2291 (2004)

    Article  Google Scholar 

  8. Bober, M.: Mpeg-7 visual shape descriptors. IEEE Trans. Circuits Syst. Video Technol. 11(6), 716–719 (2001)

    Article  Google Scholar 

  9. Bunke, H., Bengio, S., Vinciarelli, A.: Offline recognition of unconstrained handwritten texts using HMMs and statistical language models. IEEE Trans. Pattern Anal. Mach. Intell. 26(6), 709–720 (2004)

    Article  Google Scholar 

  10. Bunke, H., Riesen, K.: Recent advances in graph-based pattern recognition with applications in document analysis. Pattern Recognit. 44(5), 1057–1067 (2011)

    Article  MATH  Google Scholar 

  11. Chaudhuri, B.B., Pal, U.: A complete printed Bangla OCR system. Pattern Recognit. 31(5), 531–549 (1998)

    Article  Google Scholar 

  12. Chhabra, A.: Graphic symbol recognition: an overview. In: Tombre, K., Chhabra, A. (eds.) Graph. Recognit. Algorithms Syst., pp. 68–79. Springer, Berlin (1998)

    Chapter  Google Scholar 

  13. Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: Proceedings of the International Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 886–893 (2005)

  14. de Campos, T.E., Babu, B.R., Varma, M.: Character recognition in natural images. In: The Proceedings of International Conference on Computer Vision Theory and Applications (VISAPP) (2009)

  15. Dholakia, J., Negi, A., Mohan, S.R.: Zone identification in the printed gujarati text. In: Proceedings of the International Conference on Document Analysis and Recognition, pp. 272–276 (2005)

  16. Dholakia, J., Yajnik, A., Negi, A.: Wavelet feature based confusion character sets for gujarati script. In: Proceedings of the International Conference on Computational Intelligence and Multimedia Applications, vol. 2, pp. 366–370 (2007)

  17. Escalera, S., Forns, A., Pujol, O., Radeva, P., Snchez, G., Llads, J.: Blurred shape model for binary and grey-level symbol recognition. Pattern Recognit. Lett. 30(15), 1424–1433 (2009)

    Article  Google Scholar 

  18. Escalera, S., Forns, A., Pujol, O., Radeva, P., Llads, J., Radeva, P.: Circular blurred shape model for multiclass symbol recognition. IEEE Trans. Syst. Man Cybern. Part B Cybern. 41(2), 497–506 (2011)

    Article  Google Scholar 

  19. Freedman, D.: Statistical Models: Theory and Practice. Cambridge University Press, Cambridge (2005)

    Google Scholar 

  20. Garain, U.: Segmentation of touching characters in printed devnagari and bangla scripts using fuzzy multifactorial analysis. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 32(4), 449–459 (2002)

  21. Gehler, P., Nowozin, S.: On feature combination for multiclass object classification. In: Proceedings of the International Conference on Computer Vision, pp. 1–8 (2009)

  22. Gonen, M., Alpaydm, E.: Multiple kernel learning algorithms. J. Mach. Learn. Res. 12, 2211–2268 (2011)

    MathSciNet  Google Scholar 

  23. Hassan, E., Chaudhury, S., Gopal, M., Dholakia, J.: Use of mkl as symbol classifier for gujarati character recognition. In: Proceedings of the 9th IAPR International Workshop on Document Analysis Systems, pp. 255–262 (2010)

  24. Indermuhle, E., Frinken, V., Bunke, H.: Mode detection in online handwritten documents using blstm neural networks. In: International Conference on Frontiers in Handwriting Recognition (ICFHR), 2012, pp. 302–307 (2012)

  25. International symbol recognition contest grec2005. http://symbcontestgrec05.loria.fr/

  26. Itti, L., Koch, C.: Feature combination strategies for saliency-based visual attention systems. J. Electron. Imaging 10(1), 161–169 (2001)

    Article  Google Scholar 

  27. Lanckriet, G.R., Cristianini, N., Bartlett, P., Ghaoui, L.E., Jordan, M.I.: Learning the kernel matrix with semidefinite programming. J. Mach. Learn. Res. 4, 27–72 (2004)

    Google Scholar 

  28. Lanckriet, G.R.G., Bie, T.D., Cristianini, N., Jordan, M.I., Noble, W.S.: A statistical framework for genomic data fusion. Bioinformatics 20(16), 2626–2635 (2004)

    Article  Google Scholar 

  29. Lazebnik, S., Schmid, C., Ponce, J.: A sparse texture representation using local affine regions. IEEE Trans. Pattern Anal. Mach. Intell. 27(8), 1265–1278 (2005)

    Article  Google Scholar 

  30. Lladós, J., Valveny, E., Sánchez, G., I, M.E.: Symbol recognition: current advances and perspectives. In: Blostein, D., Kwon, Y.B. (eds.) Graphics Recognition. Algorithms and Applications, pp. 105–127. Springer, Berlin (2002)

    Google Scholar 

  31. Luqman, M.M., Delalandre, M., Brouard, T., Ramel, J.Y., Lladós, J.: Fuzzy intervals for designing structural signature: an application to graphic symbol recognition. In: Proceedings of the 8th international conference on Graphics recognition: achievements, challenges, and evolution, pp. 12–24 (2010)

  32. Majumdar, A.: Bangla basic character recognition using digital curvelet transform. Journal of Pattern Recognition Research 1, 17–26 (2007)

    Google Scholar 

  33. Mpeg-7 ce shape-1: Part b. http://www.cis.temple.edu/latecki/TestData/mpeg7shapeB.tar.gz

  34. Nilsback, M.E., Zisserman, A.: A visual vocabulary for flower classification. In: The Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 1447–1454 (2006)

  35. Pal, U., Chaudhuri, B.: Ocr in bangla: an indo-bangladeshi language. In: Pattern Recognition, 1994, Vol. 2—Conference B: Conference on Computer Vision Image Processing. Proceedings of the 12th IAPR International, Vol. 2, pp. 269–273 (1994)

  36. Pal, U., Roy, P.P., Tripathy, N., Llads, J.: Multi-oriented Bangla and Devnagari text recognition. Pattern Recogn. 43(12), 4124–4136 (2010)

    Article  MATH  Google Scholar 

  37. Platt, J.C., Cristianini, N., Taylor, J.S.: Large margin dags for multiclass classification. Adv. Neural Inf. Process. Syst. 12, 547–553 (2000)

    Google Scholar 

  38. Rakotomamonjy, A., Bach, F., Canu, S., Grandvalet, Y.: More efficiency in multiple kernel learning. Proc. Int. Conf. Mach. Learn. 772, 775–782 (2007)

    Google Scholar 

  39. Ray, A.K., Chatterjee, B.: Design of a nearest neighbor classifier system for bengali character recognition. J. IETE 30(6), 226–229 (1984)

    Google Scholar 

  40. Rozenfeld, A., Pflatz, J.L.: Sequential operations in digital picture processing. J. Assoc. Comput. Mach. 13(4), 471–494 (1966)

    Article  Google Scholar 

  41. Scalzo, F., Bebis, G., Nicolescu, M., Loss, L., Tavakkoli, A.: Feature fusion hierarchies for gender classification. In: Proceedings of International Conference on Pattern Recognition, pp. 1–4 (2008)

  42. Sonneburg, S., Ratsch, G., Schafer, C., Scholkopf, B.: Large scale multiple kernel learning. J. Mach. Learn. Res. 7, 1531–1565 (2006)

  43. Su, F., Lu, T., Yang, R.: Symbol recognition by multiresolution shape context matching. In: Proceedings of the International Conference on Document Analysis and Recognition pp. 1319–1323 (2011)

  44. Sun, X., Chen, M., Hauptmann, A.: Action recognition via local descriptors and holistic features. In: Proceedings of IEEE Computer Vision and Pattern Recognition Workshops, pp. 58–65 (2009)

  45. Sun, Q.S., Zeng, S.G., Liu, Y., Heng, P.A., Xia, D.S.: A new method of feature fusion and its application in image recognition. Pattern Recogn. 38(12), 2437–2448 (2005)

    Article  Google Scholar 

  46. Sural, S., Das, P.K.: An MLP using Hough transform based fuzzy feature extraction for Bengali script recognition. Pattern Recogn. Lett. 20(8), 771–782 (1999)

    Article  Google Scholar 

  47. Vedaldi, A., Gulshan, V., Varma, M., Zisserman, A.: Multiple kernels for object detection. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 606–613 (2009)

  48. Zhang, W., Shan, S., Gao, W., Chang, Y., Cao, B., Yang, P.: Information fusion in face identification. In: Proceedings of the 17th International Conference on Pattern Recognition, vol. 3, pp. 950–953 Vol. 3 (2004)

  49. Zhao, H., Robles-Kelly, A., Zhou, J., Lu, J., Yang, J.Y.: Graph attribute embedding via riemannian submersion learning. Comput. Vis. Image Underst. 115(7), 962–975 (2011)

    Article  Google Scholar 

  50. Zimmermann, M., Chappelier, J.C., Bunke, H.: Offline grammar-based recognition of handwritten sentences. IEEE Trans. Pattern Anal. Mach. Intell. 28(5), 818–821 (2006)

    Article  Google Scholar 

  51. Zolnay, A., Schlueter, R., Ney, H.: Acoustic feature combination for robust speech recognition. In: Proceedings of International Conference on Acoustics, Speech, and Signal Processing, Vol. 1, pp. 457–460 (2005)

Download references

Acknowledgments

Authors are thankful to Prof. BB Chaudhuri, ISI Kolkata, and Prof. S Ramamohan, MSU Baroda, for providing the Bangla and the Gujarati character/symbol data set. The work was supported under the project sponsored by DIT, Government of India.

Author information

Authors and Affiliations

  1. Department of Electrical Engineering, IIT Delhi, New Delhi, India

    Ehtesham Hassan & Santanu Chaudhury

  2. School of Engineering, Shiv Nadar University, Gautam Buddha Nagar, Uttar Pradesh, India

    M. Gopal

Authors
  1. Ehtesham Hassan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Santanu Chaudhury
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. M. Gopal
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ehtesham Hassan.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hassan, E., Chaudhury, S. & Gopal, M. Feature combination for binary pattern classification. IJDAR 17, 375–392 (2014). https://doi.org/10.1007/s10032-014-0224-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10032-014-0224-9

Keywords

Search

Navigation