Skip to main content
SpringerLink
Log in

RETRACTED ARTICLE: Offline scripting-free author identification based on speeded-up robust features

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

This article was retracted on 10 June 2022

This article has been updated

Abstract

This article proposes offline language-free writer identification based on speeded-up robust features (SURFs), which goes through training, enrollment, and identification stages. In all stages, an isotropic box filter is first used to segment the handwritten text image into word regions (WRs). Then, the SURF descriptors (SUDs) of WR and the corresponding scales and orientations (SOs) are extracted. In the training stage, an SUD codebank is constructed by clustering the SUDs of training samples. In the enrollment stage, the SUDs of the input handwriting adopted to form an SUD signature (SUDS) by looking up the SUD codebank and the SOs are utilized to generate a scale and orientation histogram \(({H}_{\mathrm{SO}})\). In the identification stage, the SUDS and \({H}_{\mathrm{SO}}\) of the input handwriting are extracted and matched with the enrolled ones for identification. Experimental results on eight public datasets demonstrate that the proposed method outperforms the state-of-the-art algorithms.

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

Similar content being viewed by others

Change history

References

  1. Zois, E., Anastassopoulos, V.: Morphological waveform coding for writer identification. Pattern Recognit. 33(3), 385–398 (2000)

    Article  Google Scholar 

  2. Tan, T., Said, H., Baker, K.: Personal identification based on handwriting. Pattern Recognit. 33(1), 149–160 (2000)

    Article  Google Scholar 

  3. Oliveira, L., Hanusiak, R., Justino, E., Sabourin, R.: Writer verification using texture-based features. Int. J. Doc. Anal. Recognit. 15(3), 213–226 (2012)

    Article  Google Scholar 

  4. Wshah, S., Kumar, G., Govindaraju, V.: Script independent word spotting in offline handwritten documents based on hidden Markov models. In: International Conference on Frontiers in Handwriting Recognition, 978-0-7695-4774-9 (2012)

  5. Moghaddam, M., Helli, B.: A text-independent Persian writer identification based on feature relation graph (FRG). Pattern Recognit. 43(6), 2199–2209 (2010)

    Article  Google Scholar 

  6. Espana-Boquera, S., Castro-Bleda, M.J., Gorbe-Moya, J., Zamora-Martinez, F.: Improving offline handwritten text recognition with hybrid HMM/ANN models. IEEE Trans. Pattern Anal. Mach. Intell. 33(4), 767–789 (2011)

    Article  Google Scholar 

  7. Ryu, J.: Il Koo, H.: Language-independent text-line extraction algorithm for handwritten documents. IEEE Signal Process. Lett. 21(9), 1115–1119 (2014)

    Article  Google Scholar 

  8. Bertolini, D., Oliveira, L., Justino, E., Sabourin, R.: Texture-based descriptors for writer identification and verification. Expert Syst. Appl. 40(6), 2069–2080 (2013)

    Article  Google Scholar 

  9. Schomaker, L., Bulacu, M.: Text-independent writer identification and verification using textural allographic features. IEEE Trans. Pattern Anal. Mach. Intell. 29(4), 701–717 (2007)

    Article  Google Scholar 

  10. Bernard, Bianne: A.L., Menasri, F., Mohamad, R.A.H.: Dynamic and contextual information in HMM modeling for handwritten word recognition. IEEE Trans. Pattern Anal. Mach. Intell. 33(10), 2066–2080 (2011)

    Article  Google Scholar 

  11. van der Zant, T.: Handwritten-word spotting using biologically inspired features. IEEE Trans. Pattern Anal. Mach. Intell. 30(11), 1945–1957 (2008)

    Article  Google Scholar 

  12. Graves, A., Liwicki, M., Fernandez, S.: A novel connectionist system for unconstrained handwriting recognition. IEEE Trans. Pattern Anal. Mach. Intell. 31(5), 855–868 (2009)

    Article  Google Scholar 

  13. Ghosh, D., Dube, T., Shivaprased, A.P.: Script recognition–a review. IEEE Trans. Pattern Anal. Mach. Intell. 32(12), 2142–2161 (2010)

    Article  Google Scholar 

  14. Lowe, D.: Distinctive image features from scale-invariant key points. Int. J. Comput. Vis. 60(2), 91–110 (2004)

    Article  Google Scholar 

  15. Nister, D., Stewenius, H.: Scalable recognition with a vocabulary tree. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 2161–2168 (2006)

  16. Jiang, Y., Ding, X., Fu, Q., Ren Z.: Context driven Chinese string segmentation and recognition. In: Proceedings of Structural, Syntactic, and Statistical Pattern Recognition: Joint IAPR Int’l Workshops, pp. 127–135 (2006)

  17. Sharma, M.K., Dhaka, V.P.: An efficient segmentation technique for Devanagari offline handwritten scripts using the feedforward neural network. Neural Comput. Appl. (2015). doi:10.1007/s00521-015-1844-9

    Article  Google Scholar 

  18. Dhaka, V.P., Sharma, M.K.: Classification of image using a genetic general neural decision tree. Int. J. Appl. Pattern Recognit. 2(1), 76–95 (2015)

    Article  Google Scholar 

  19. Obaidullah, S.M., Mondal, A., Roy, K.: Structural feature based approach for script identification from printed Indian document. In: IEEE International Conference on Signal Processing and Integrated Networks (SPIN), pp. 120–124 (2014)

  20. Zhu, G., Zheng, Y., Doermann, D., Jaeger, S.: Signature detection and matching for document image retrieval. IEEE Trans. Pattern Anal. Mach. Intell. 31(11), 2015–2031 (2009)

    Article  Google Scholar 

  21. You, J., Zhang, D., Cao, J., Guo, M.: Parallel biometrics computing using mobile agents. In: IEEE International Conference on Parallel Processing, pp. 305–312 (2003)

  22. Pervouchine, V.: Sch. of Comput. Eng., Nanyang Technol. Univ., Singapore; Leedham, G., “Document Examiner Feature Extraction: Thinned vs. Skeletonised Handwriting Images”, TENCON 2005 IEEE. Region 10, 1–6 (2005)

    Google Scholar 

  23. Tomai, C.I., Zhang, B., Srihari, S.N.: Discriminatory power of handwritten words for writer recognition. In: Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004, vol. 2, pp. 638–641 (2004)

  24. Sharma, M.K., Dhaka, V.P.: Segmentation of English offline handwritten cursive scripts using a feedforward neural network. Neural Comput. Appl. (2015). doi:10.1007/s00521-015-1940-x

    Article  Google Scholar 

  25. Sharma, M.K., Dhaka, V.P.: Pixel plot and trace based segmentation method for bilingual handwritten scripts using feedforward neural network. Neural Comput. Appl. (2015). doi:10.1007/s00521-015-1972-2

    Article  Google Scholar 

  26. Sharma, M.K., Dhaka, V.P.: Offline language-free writer identification based on speeded-up robust features. In: International Journal of Engineering (IJE), IJE Transactions A: Basics, vol. 28, No. (7) (2015)

  27. Fink, G., Plotz, T.: On the use of context-dependent modeling units for HMM-based offline handwriting recognition. Proceedings of International Conference Document Analysis and Recognition 2, 729–733 (2007)

    Google Scholar 

  28. Safabakhsh, R., Ghiasi, G.: Offline text-independent writer identification using codebank and efficient code extraction methods. Image Vis. Comput. 31(5), 379–391 (2013)

    Article  Google Scholar 

  29. Doermann, D., Jain, R.: Offline writer identification using k-adjacent segments. In: Proceedings of the International Conference Document Analysis and Recognition, pp. 769–773 (2011)

  30. Siddiqi, I., Djeddi, C., Souici-Meslati, L., Ennaji, A.: Text-independent writer recognition using multi-script handwritten texts. Pattern Recognit. Lett. 34(10), 1196–1202 (2013)

    Article  Google Scholar 

  31. Srihari, S., Cha, S., Arora, H., Lee, S.: Individuality of handwriting. J. Forensic Sci. 47(4), 856–872 (2002)

    Article  Google Scholar 

  32. Gatos, B., Louloudis, G., Pratikakis, I., Halatsis, C.: Text line and word segmentation of handwritten documents. Pattern Recognit. 42(12), 3169–3183 (2009)

    Article  Google Scholar 

  33. Stafylakis, T., Papavassiliou, V., Katsouros, V., Carayann, G.: Handwritten document image segmentation into text lines and words. Pattern Recognit. 43(1), 369–377 (2010)

    Article  Google Scholar 

  34. Bay, H., Ess, A., Tuytelaars, T., Van Gool, L.: Speeded-up robust features (SURF). Int. J. Comput. Vis. Image Underst. 110, 346–359 (2008)

    Article  Google Scholar 

  35. Mumtaz, A., Coviello, E., Lanckriet, G.R.G., Chan, A.B.: Clustering dynamic textures with the hierarchical EM algorithm for modeling clustering dynamic textures with the hierarchical EM algorithm for modeling video. Int. J. Pattern Anal. Mach. Intell. IEEE 35(7), 1606–1621 (2013)

  36. Viard-Gaudin, C., Tan, G., Kot, A.: Automatic writer identification framework for online handwritten documents using character prototypes. Pattern Recognit. 42(12), 3313–3323 (2009)

    Article  Google Scholar 

  37. Krivulin, N.: Algebraic solution to a constrained rectilinear minimax location problem on the plane. In: International Conference on Multimedia Technology (ICMT), IEEE, pp. 6216–6220 (2011)

  38. Karayiannis, N.B., Randolph-Gips, M.M.: Soft learning vector quantization and clustering algorithms based on non-Euclidean norms: multinorm algorithms. IEEE Trans. Neural Netw. 14(1), 89–102 (2003)

    Article  Google Scholar 

  39. Honkela, T., Duch, W., Girolami, M., Kaski, S.: Artificial neural networks and machine learning-ICANN2011. In: 21th International Conference on Artificial Neural Networks, Espoo, Finland, Proceedings Part I. Springer (2011)

  40. Marti, U., Bunke, H.: The IAM-database: an English sentence database for offline handwriting recognition. Int. J. Doc. Anal. Recognit. 5(1), 39–46 (2002)

    Article  Google Scholar 

  41. Bulacu, M., Schomaker, L., Vuurpijl, L.: Writer identification using edge-based directional features. In: Proceedings of the 7th International Conference Document Analysis and Recognition (ICDAR \(\backslash \)’03), pp. 937–941 (2003)

  42. Guyon, I., Schomaker, L., Plamondon, R., Liberman, M., Janet, S.: UNIPEN project of on-line data exchange and recognizer benchmarks. In: Proceedings of the International Conference on Pattern Recognition, pp. 29–33 (1994)

  43. Su, T., Zhang, T., Guan, D.: Corpus-based HIT-MW database for offline recognition of general-purpose Chinese handwritten text. Int. J. Doc. Anal. Recognit. (ICDAR \(\backslash \)’03) 10(1), 27–38 (2007)

  44. Louloudis, G., Gatos, B., Stamatopoulos, N.: ICFHR 2012 competition on writer identification challenge 1: Latin/Greek documents. In: Proceedings of the International Conference on Frontiers in Handwriting Recognition, pp. 829–834 (2012)

  45. Louloudis, G., Stamatopoulos, N., Gatos, B.: ICDAR 2011 writer identification contest. In: Proceedings of the International Conference on Document Analysis and Recognition, pp. 1475–1479 (2011)

  46. Hassaine, A., Maadeed, S., Alja’am, J., Jaoua, A., Bouridane, A.: The ICDAR2011 Arabic writer identification contest. In: Proceedings of the International Conference on Document Analysis and Recognition, pp. 1470–1474 (2011)

  47. Fornes, A., Dutta, A., Gordo, A., Llados, J.: The ICDAR 2011 music scores competition: staff removal and writer identification. In: Proceedings of the International Conference on Document Analysis and Recognition, pp. 1511–1515 (2011)

  48. Hassaine, A., Maadeed, S.: ICFHR 2012 competition on writer identification challenge 2: Arabic scripts. In: Proceedings of the International Conference on Frontiers in Handwriting Recognition, pp. 835–840 (2012)

  49. Li, X., Ding, X.: Writer identification of Chinese handwriting using grid microstructure feature. In: Proceedings of the 3rd ICB, pp. 1230–1239 (2009)

  50. Brink, A., Smit, J., Bulacu, M., Schomaker, L.: Writer identification using directional ink-trace width measurements. Pattern Recognit. 45(1), 162–171 (2012)

    Article  Google Scholar 

  51. Siddiqi, I., Vincent, N.: Text independent writer recognition using redundant writing patterns with contour-based orientation and curvature features. Pattern Recognit. 43(11), 3853–3865 (2010)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Jaipur National University, Jagatpura, Jaipur, Rajasthan, 302017, India

    Manoj Kumar Sharma & Vijay Pal Dhaka

Authors
  1. Manoj Kumar Sharma
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Vijay Pal Dhaka
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Manoj Kumar Sharma.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sharma, M.K., Dhaka, V.P. RETRACTED ARTICLE: Offline scripting-free author identification based on speeded-up robust features. IJDAR 18, 303–316 (2015). https://doi.org/10.1007/s10032-015-0252-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10032-015-0252-0

Keywords

Search

Navigation