Deep bidirectional long short-term memory for online multilingual writer identification based on an extended Beta-elliptic model and fuzzy elementary perceptual codes

Abstract

The development of pattern recognition and artificial intelligence domains owes the writer identification challenge greatly. In fact, writer identification is still a challenging task in the definition of a set of features able to characterize the various handwritten documents. These handwritten documents are not generally stable and show a wide variability from the same person over time, or from different writers. The capacity to identify the documents’ writers provides further chances of using these handwritten documents for several applications like forensic science, control access, digital rights management and financial transactions. In this paper, we propose a novel system to text-independent online multilingual writer identification. Our system is based on new model that we named the Extended Beta-Elliptic Model. Moreover, we are interested in using the Fuzzy Elementary Perceptual Codes to characterize the handwriting of writers well. In addition, we adopted the use of Recurrent Neural Network with Deep Bidirectional Long Short-Term Memory in the training and identification phases. Experiments are conducted on IBM_UB_1 and ADAB datasets with 98.44% and 100% writer identification rates respectively. The proposed system using the combination of the Extended Beta-Elliptic model and the Fuzzy Elementary Perceptual Codes in features extraction and the Deep Bidirectional Long Short-Term Memory in classification outperforms the existing online writer identification systems on both Latin and Arabic scripts.

This is a preview of subscription content, access via your institution.

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
Fig. 20
Fig. 21
Fig. 22
Fig. 23

References

  1. 1.

    Alimi AM (2003) Beta neuro-fuzzy systems. TASK Quarterly J, Special Issue Neural Netw 7(1):23–41

    Google Scholar 

  2. 2.

    Batool F E, Attique M, Sharif M, Javed K, Nazir M, Abbasi A A, Iqbal Z and Riaz N (2020) Offline signature verification system: a novel technique of fusion of GLCM and geometric features using SVM. Multimed Tools Appl, 1–20

  3. 3.

    Boubaker H, Rezzoug N, Kherallah M, Gorce P, Alimi AM (2015) Spatiotemporal representation of 3D hand trajectory based on Beta-elliptic models. CMBBE 18(15):1632–1647

    Google Scholar 

  4. 4.

    Boubaker H, Tagougui N, El Abed H, Kherallah M, Alimi AM (2014) Graphemes Segmentation for Arabic Online Handwriting Modeling. JIPS 10(4):503–522

    Google Scholar 

  5. 5.

    Boubaker H, Elbaati A, Tagougui N, El Abed H, Kherallah M and Alimi A M (2012) Online Arabic databases and applications. Guide to OCR for Arabic Scripts, pp. 541–557. Springer, London.

  6. 6.

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

    Article  Google Scholar 

  7. 7.

    Chapran J (2006) Biometric writer identification: feature analysis and classification. Int J Pattern Recognit Artificial Intell 20(04):483–503

    Article  Google Scholar 

  8. 8.

    Chen F, Xu W, Bai C, Gao X (2016) A novel approach to guarantee good robustness of fuzzy reasoning. Appl Soft Comput 41:224–234

    Article  Google Scholar 

  9. 9.

    Cilia ND, De Stefano C, Fontanella F, Marrocco C, Molinara M, Di Freca AS (2020) An end-to-end deep learning system for medieval writer identification. Pattern Recognit Lett 129:137–143

    Article  Google Scholar 

  10. 10.

    Dhieb T, Njah S, Boubaker H, Ouarda W, Ayed MB, Alimi AM (2020) Towards a novel biometric system for forensic document examination. Comput Secur 97:101973. https://doi.org/10.1016/j.cose.2020.101973

  11. 11.

    Dhieb T, Rezzoug N, Boubaker H, Gorce P, Alimi AM (2019) Effect of age on hand drawing movement kinematics. Comput Methods Biomech Biomed Eng 22(sup1):S188–S190. https://doi.org/10.1080/10255842.2020.1714235

  12. 12.

    Dhieb T, Boubaker H, Ouarda W, Ayed MB, Alimi AM (2019) Deep bidirectional long short-term memory for online Arabic writer identification based on beta-elliptic model. 2019 International Conference on Document Analysis and Recognition Workshops 6:35–40. https://doi.org/10.1109/ICDARW.2019.50113

  13. 13.

    Dhieb T, Ouarda W, Boubaker H, Alimi AM (2016) Beta-Elliptic Model for Writer Identification from Online Arabic Handwriting. Journal of Information Assurance & Security (JIAS), Vol. 11 Issue 5, pp. 263–272, Link: https://www.mirlabs.org/jias/secured/Volume11-Issue5/Paper27.pdf

  14. 14.

    Dhieb T, Ouarda W, Boubaker H, Alimi A M (2016) Deep neural network for online writer identification using beta-elliptic model. 2016 International Joint Conference on Neural Networks (IJCNN). IEEE, pp 1863–1870. https://doi.org/10.1109/IJCNN.2016.7727426

  15. 15.

    Dhieb T, Ouarda W, Boubaker H, Halima MB, Alimi AM (2015) Online Arabic writer identification based on beta-elliptic model. 2015 15th International Conference on Intelligent Systems Design and Applications. IEEE, pp 74–79. https://doi.org/10.1109/ISDA.2015.7489203

  16. 16.

    Dhieb T, Njah S, Boubaker H, Ouarda W, Ayed MB, Alimi AM (2018) An online writer identification system based on beta-elliptic model and fuzzy elementary perceptual codes. arXiv preprint arXiv:1804.05661

  17. 17.

    El Abed H, Kherallah M, Märgner V, Alimi AM (2011) On-line arabic handwriting recognition competition. Int J Document Anal Recognit (IJDAR) 14(1):15–23

    Article  Google Scholar 

  18. 18.

    Gianaria E, Grangetto M (2019) Robust gait identification using Kinect dynamic skeleton data. Multimed Tools Appl 78(10):13925–13948

    Article  Google Scholar 

  19. 19.

    Hashad FG, Zahran O, El-Rabaie ESM, Elashry IF, El-Samie FEA (2019) Fusion-based encryption scheme for cancelable fingerprint recognition. Multimed Tools Appl 78(19):27351–27381

    Article  Google Scholar 

  20. 20.

    Hassan E, Chaudhury S, Yadav N, Kalra P, Gopal M (2014) Off-line hand written input based identity determination using multi kernel feature combination. Pattern Recognit Lett 35:113–119

    Article  Google Scholar 

  21. 21.

    Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural comput 9(8):1735–1780

    Article  Google Scholar 

  22. 22.

    Jagtap A B, Sawat D D, Hegadi R S and Hegadi R S (2020) Verification of genuine and forged offline signatures using Siamese Neural Network (SNN). Multimed Tools Appl

  23. 23.

    Kherallah M, Tagougui N, Alimi A M, El Abed H and Margner V (2011) Online Arabic handwriting recognition competition. 2011 International Conference on Document Analysis and Recognition (ICDAR), pp. 1454–1458, IEEE.

  24. 24.

    Kingma D P and Ba J (2014) Adam: A method for stochastic optimization. Proceedings of the 3rd International Conference on Learning Representations (ICLR), arXiv preprint arXiv (Vol. 1412).

  25. 25.

    Kumar R, Chanda B, Sharma JD (2014) A novel sparse model based forensic writer identification. Pattern Recognit Lett 35:105–112

    Article  Google Scholar 

  26. 26.

    Li B, Tan T (2009) Online Text-independent Writer Identification Based on Temporal Sequence and Shape Codes. ICDAR 2009:931–935

    Google Scholar 

  27. 27.

    Liang Y, Fairhurst MC, Guest RM, Erbilek M (2016) Automatic Handwriting Feature Extraction, Analysis and Visualization in the Context of Digital Palaeography. Int. J. Pattern Recognit Artificial Intell 30(04):1653001

    Article  Google Scholar 

  28. 28.

    Liwicki M, Schlapbach A, Bunke H, Bengio S, Mariéthoz J, Richiardi J (2006) Writer identification for smart meeting room systems. International Workshop on Document Analysis Systems, pp.186–195, Springer, Berlin, Heidelberg

  29. 29.

    Nguyen HT, Nguyen CT, Ino T, Indurkhya B, Nakagawa M (2019) Text-independent writer identification using convolutional neural network. Pattern Recognit Lett 121:104–112

    Article  Google Scholar 

  30. 30.

    Njah S, Bezine H and Alimi AM (2013) Linguistic Interpretation for On-line Handwriting using PerTOHS Theory. 16th Int. Graphonomics Society (IGS), pp.175–178

  31. 31.

    Njah S, Ltaief M, Bezine H and Alimi AM (2012) The PerTOHS Theory for On-Line Handwriting Segmentation. International Journal of Computer Science Issues (IJCSI), Vol. 9, Issue 5, No 3, pp.142–151, Link: http://www.ijcsi.org/papers/IJCSI-9-5-3-142-151.pdf

  32. 32.

    Njah S, Bezine H and Alimi AM (2011) A fuzzy genetic system for segmentation of on-line handwriting: Application to ADAB database. 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS). pp. 95–102, IEEE

  33. 33.

    Ouarda W, Trichili H, Alimi, AM and Solaiman B (2015) Bag of Face Recognition Systems based on Holistic Approaches, 2015 15th International Conference on Intelligent Systems Design and Applications (ISDA), pp. 201–206, IEEE

  34. 34.

    Ouarda W, Trichili H, Alimi AM, Solaiman B (2014) MLP Neural Network for face recognition based on Gabor Features and Dimensionality Reduction techniques, 2014 International Conference on Multimedia Computing and Systems (ICMCS), pp. 127–134, IEEE

  35. 35.

    Plamondon R, Lorette G (1989) Automatic Signature Verification and Writer Identification—The State of the Art. Pattern Recognit 22(2):107–131

    Article  Google Scholar 

  36. 36.

    Rehman A, Naz S, Razzak MI (2019) Writer identification using machine learning approaches: a comprehensive review. Multimed Tools Appl 78(8):10889–10931

    Article  Google Scholar 

  37. 37.

    Ren Y, Fang Z, Liu D, Chen C (2019) Replay attack detection based on distortion by loudspeaker for voice authentication. Multimed Tools Appl 78(7):8383–8396

    Article  Google Scholar 

  38. 38.

    Schlapbach A, Liwicki M, Bunke H (2008) A writer identification system for on-line whiteboard data. Pattern recognit 41(7):2381–2397

    Article  Google Scholar 

  39. 39.

    Schomaker L, Bulacu M (2004) Automatic writer identification using connected-component contours and edge-based features of uppercase western script. IEEE Trans. Pattern Anal. Mach. Intell. 26(6):787–798

    Article  Google Scholar 

  40. 40.

    Schuster M, Paliwal KK (1997) Bidirectional recurrent neural networks. IEEE trans Signal Process 45(11):2673–2681

    Article  Google Scholar 

  41. 41.

    Seidler RD (2006) Differential Effects of Age on Sequence Learning and Sensorimotor Adaptation. Brain Res Bull 70(4–6):337–346. https://doi.org/10.1016/j.brainresbull.2006.06.008

    Article  Google Scholar 

  42. 42.

    Shivram A, Ramaiah C, Govindaraju V (2014) Data Sufficiency for Online Writer Identification: A Comparative Study of Writer-Style Space vs. Feature Space Models, 2014 22nd International Conference on Pattern Recognition pp. 3121–3125, IEEE

  43. 43.

    Shivram A, Ramaiah C, Setlur S, Govindaraju V (2013) IBM_UB_1: a dual mode unconstrained English handwriting dataset. ICDAR 2013, pp. 13–17

  44. 44.

    Shivram A, Ramaiah C, Porwal U, Govindaraju V (2012) Modeling Writing Styles for Online Writer Identification: A Hierarchical Bayesian Approach, 2012 International Conference on Frontiers in Handwriting Recognition, pp. 387–392, IEEE

  45. 45.

    Singh G, Sundaram S (2015) A Subtractive Clustering Scheme for Text-Independent Online Writer Identification. ICDAR 2015:311–315

    Google Scholar 

  46. 46.

    Sreeraj M, Idicula SM (2011) A survey on writer identification schemes. Int J Comput Appl 26(2):23–33

    Google Scholar 

  47. 47.

    Venugopal V, Sundaram S (2018) An improved online writer identification framework using codebook descriptors. Pattern Recognit 78:318–330

    Article  Google Scholar 

  48. 48.

    Venugopal V, Sundaram S (2018) Online Writer Identification With Sparse Coding-Based Descriptors. IEEE Trans Inf Forensics Secur 13(10):2538–2552

    Article  Google Scholar 

  49. 49.

    Venugopal V, Sundaram S (2017) An online writer identification system using regression-based feature normalization and codebook descriptors. Expert Syst Appl 72:196–206

    Article  Google Scholar 

  50. 50.

    Wang X, Wang L, Li S, Wang J (2018) An event-driven plan recognition algorithm based on intuitionistic fuzzy theory. J Supercomput 74(12):6923–6938. https://doi.org/10.1007/s11227-018-2650-9

    Article  Google Scholar 

  51. 51.

    Yang W, Jin L, Liu M (2016) DeepWriterID: An End-to-End Online Text-Independent Writer Identification System. IEEE Intell Syst 31(2):45–53

    MathSciNet  Article  Google Scholar 

Download references

Acknowledgments

The research leading to these results has received funding from the Ministry of Higher Education and Scientific Research of Tunisia under the grant agreement number LR11ES4.

Funding

This study was funded by the Ministry of Higher Education and Scientific Research of Tunisia (grant number LR11ES4).

Author information

Affiliations

Authors

Corresponding author

Correspondence to Thameur Dhieb.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethics approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Dhieb, T., Boubaker, H., Ouarda, W. et al. Deep bidirectional long short-term memory for online multilingual writer identification based on an extended Beta-elliptic model and fuzzy elementary perceptual codes. Multimed Tools Appl (2021). https://doi.org/10.1007/s11042-020-10412-8

Download citation

Keywords

  • Online writer identification
  • Deep Bidirectional Long Short-Term Memory
  • Extended Beta-Elliptic Model
  • Fuzzy Elementary Perceptual Codes