Forensic Analysis of Manuscript Authorship: An Optimized Computational Approach Based on Texture Descriptors

  • Jean Felipe Felsky
  • Edson J. R. JustinoEmail author
  • Jacques Facon
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10029)


This paper presents an optimized method for establishing the authorship of questioned handwritten documents, on the basis of a forensic analysis and a computational model using texture descriptors. The proposed method uses two classes of texture descriptors: model-based, using fractal geometry, and statistical, using GLCM (Gray-Level Co-occurrence Matrix) and Haralick’s descriptors. The proposed method also uses an SVM (Support Vector Machine) as a classifier and generator of the writer-independent training. The results demonstrate the robustness of the writer-independent obtained from the features by using texture descriptors and robustness in the amount low of samples used as references for comparison and the number of feature used. The results appear promising, in the order of 97.7 %, and are consistent with those obtained in other studies that used the same database.


Handwritten Document Classifier Texture Descriptors 


  1. 1.
    Bertolini, D., Oliveira, L.S., Justino, E., Sabourin, R.: Texture-based descriptors for writer identification and verification. Expert Syst. Appl. 40, 2069–2080 (2013)CrossRefGoogle Scholar
  2. 2.
    Hanusiak, R.K., Oliveira, L.S., Justino, E., Sabourin, R.: Writer verification using texture-based features. Int. J. Doc. Anal. Recogn. 15, 213–226 (2012)CrossRefGoogle Scholar
  3. 3.
    Siddiqi, I., Vincent, N.: Text independent writer recognition using redundant writing patterns with contour-based orientation and curvature features. Pattern Recogn. 43, 3853–3865 (2010)CrossRefzbMATHGoogle Scholar
  4. 4.
    Shomaker, L.: Advances in writer identification and verification. In: Proceedings of the International Conference on Document Analysis and Recognition (ICDAR), Curitiba, Brazil (2007)Google Scholar
  5. 5.
    Schlapbach, A., Bunke, H.: A writer identification and verification system using HMM based recognizers. Pattern Anal. Appl. 10, 33–43 (2007)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Bush, A., Boles, W., Sridharan, S.: Texture for script identification. IEEE Trans. Pattern Anal. Mach. Intell. 27(11), 1721–1732 (2005)Google Scholar
  7. 7.
    Bensefia, A., Paquet, T., Heutte, L.: A writer identification and verification system. Pattern Recogn. Lett. 26(13), 2080–2092 (2005)CrossRefzbMATHGoogle Scholar
  8. 8.
    Schlapbach, A., Bunke, H.: Using HMM based recognizers for writer identification and verification. In: Ninth International Workshop on Frontiers in Handwriting Recognition, pp. 67–172 (2004)Google Scholar
  9. 9.
    Bulacu, M., Shomaker, L.: Writer identification using edge-based directional features. In: Proceedings of 7th International Conference on Document Analysis and Recognition (ICDAR). IEEE Computer Society (2003)Google Scholar
  10. 10.
    Cha, S.H.: Use of the distance measures in handwriting analysis. Doctor Theses. State University of New York at Buffalo, EUA, 208 (2001) Google Scholar
  11. 11.
    Samarabandu, J., et al.: Analysis of bone X-rays using morphological fractals. IEEE Trans. Med. Imaging 12(3), 466–470 (1993)CrossRefGoogle Scholar
  12. 12.
    Serra, J.: Image Analysis and Mathematical Morphology, vol. 1. Academic Press, Cambridge (1982)zbMATHGoogle Scholar
  13. 13.
    Mandelbrot, B.B.: The Fractal Geometry of Nature. W.H. Freeman, London (1977)zbMATHGoogle Scholar
  14. 14.
    Haralick, R.M., Shanmugam, K., Dinstein, I.: Textural features for image classification. IEEE Trans. Syst. Cyber. smc-3(6), 610–621 (1973)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Jean Felipe Felsky
    • 1
  • Edson J. R. Justino
    • 1
    Email author
  • Jacques Facon
    • 1
  1. 1.Pontifícia Universidade Católica do Paraná (PUCPR) Rua Imaculada ConceicaoCuritibaBrazil

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