CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

A Survey on Writer Identification Schemes

by Sreeraj.M, Sumam Mary Idicula
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 26 - Number 2
Year of Publication: 2011
Authors: Sreeraj.M, Sumam Mary Idicula
10.5120/3075-4205

Sreeraj.M, Sumam Mary Idicula . A Survey on Writer Identification Schemes. International Journal of Computer Applications. 26, 2 ( July 2011), 23-33. DOI=10.5120/3075-4205

@article{ 10.5120/3075-4205,
author = { Sreeraj.M, Sumam Mary Idicula },
title = { A Survey on Writer Identification Schemes },
journal = { International Journal of Computer Applications },
issue_date = { July 2011 },
volume = { 26 },
number = { 2 },
month = { July },
year = { 2011 },
issn = { 0975-8887 },
pages = { 23-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume26/number2/3075-4205/ },
doi = { 10.5120/3075-4205 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:11:47.470880+05:30
%A Sreeraj.M
%A Sumam Mary Idicula
%T A Survey on Writer Identification Schemes
%J International Journal of Computer Applications
%@ 0975-8887
%V 26
%N 2
%P 23-33
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a survey of the literature on writer identification schemes and techniques up till date. The paper outlines an overview of the writer identification schemes mainly in Chinese, English, Arabic and Persian languages. Taxonomy of different features adopted for online and offline writer identification schemes is also drawn at. The feature extraction methods adopted for the schemes are discussed in length outlining the merits and demerits of the same. In automated writer identification, text independent and text dependent methods are available which is also discussed in this paper. An evaluation of writer identification schemes under multiple languages is also analyzed by comparing the recognition rate.

References
  1. Fornes, A., Llados, J., Sanchez, G., Bunke, H. (2008).Writer Identification in Old Handwritten Music Scores. In: 8th IAPR Workshop on Document Analysis Systems, 347—353.
  2. Sas, J. (2006) Handwriting Recognition Accuracy Improvement by Author Identification. In: L. Rutkowski et al. (eds.), ICAISC 2006, LNAI 4029, 682--691.Springer, Heidelberg.
  3. Chaudhry, R., Pant, S. K. (2004) Identification of authorship using lateral palm print—a new concept. J.ForensicScience International, volume (141), 49--57.
  4. Schomaker, L. (2007) Advances in Writer Identification and Verification. In: 9th International Conference on Document Analysis and Recognition (ICDAR’07), volume (2), 1268--1273.
  5. Plamondon, R., Lorette, G. (1989) “Automatic Signature Verification and Writer Identification—The State of the Art,” Pattern Recognition, vol. 22, no. 2, pp. 107-131.
  6. Leclerc, F., Plamondon, R. (1994) Automatic signature verification: The state of the art 1989-1993. In Progress in Automatic Signature Verification edited by R. Plamandon, World Scientific Publ. Co., pp. 13-19.
  7. Gupta, S. (2008).Automatic Person Identification and Verification using Online Handwriting. Master Thesis. International Institute of Information Technology Hyderabad, India
  8. Schlapbach, A., Marcus, L. Bunke, H. (2008) A writer identification system for on-line whiteboard data, Pattern Recognition Journal 41 (2008) 23821–23897.
  9. Schomaker, L. (2007) Advances in Writer identification and verification, in: Ninth International Conference on Document Analysis and Recognition (ICDAR).
  10. Li, B., Sun, Z., Tan, T.N. (2007) Hierarchical Shape Primitive Features for Online Text-independent Writer Identification, Proc. of 2th ICB, pages 201–210.
  11. Yan, Y., Chen, Q., Deng, W., Yuan, F. (2009) “Chinese Handwriting Identification Based on Stable Spectral Feature of Texture Images” International Journal of Intelligent Engineering and Systems, Vol.2, No.1.
  12. He, Z., You, X., Tang, Y.Y. (2008) Writer identification of Chinese handwriting documents using hidden Markov tree model, Pattern Recognition Journal 41, 1295–13072008-06-15.
  13. Zhenyu, H., Xinge, Y., Tang, Y.Y. (2008)Writer Identification using global wavelet-based features, Neurocomputing 71, 1832–1841.
  14. Said, H., Tan, T., Baker, K. (2000) “Personal Identification Based on Handwriting,” Pattern Recognition, vol. 33, no. 1, pp. 149-160.
  15. Said, H., Peake, G., Tan, T., Baker, K. (1998) “Writer Identification from Non-Uniformly Skewed Handwriting Images,” Proc. Ninth British Machine Vision Conf., pp. 478-487.
  16. Tan, T. (1998) “Rotation Invariant Texture Features and Their Use in Automatic Script Identification,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 7, pp. 751-756.
  17. Zhu, Y., Tan, T., Wang, Y. (2001) “Font Recognition Based on Global Texture Analysis,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 23, no. 10, pp. 1192-1200.
  18. Zois, E., Anastassopoulos, V. (2000) “Morphological Waveform Coding for Writer Identification,” Pattern Recognition, vol. 33, no. 3, pp. 385-398.
  19. Srihari, S., Cha, S., Arora, H., Lee, S. (2002) “Individuality of Handwriting,” J. Forensic Sciences, vol. 47, no. 4, pp. 1-17.
  20. Srihari, S., Beal, M., Bandi, K., Shah, V., Krishnamurthy, P. (2005) “A Statistical Model for Writer Verification,” Proc. Eighth Int’l Conf. Document Analysis and Recognition (ICDAR), pp. 1105-1109.
  21. Favata, J., Srikantan, G. (1996). “A Multiple Feature/Resolution Approach to Hand printed Digit and Character Recognition,” Int’l J. Imaging Systems and Technology, vol. 7, pp. 304-311.
  22. Zhang, B., Srihari, S., Lee, S. (2003) “Individuality of Handwritten Characters,” Proc. Seventh Int’l Conf. Document Analysis and Recognition (ICDAR), pp. 1086-1090.
  23. Srihari, S., Tomai, C., Zhang, B., Lee, S. (2003) “Individuality of Numerals,” Proc. Seventh Int’l Conf. Document Analysis and Recognition (ICDAR), pp. 1096-1100.
  24. Zhang, B., Srihari, S. (2003) “Analysis of Handwritten Individuality Using Word Features,” Proc. Seventh Int’l Conf. Document Analysis and Recognition (ICDAR), pp. 1142-1146.
  25. Tomai, C., Zhang, B., Srihari, S. (2004) “Discriminatory Power of Handwritten Words for Writer Recognition,” Proc. 17th Int’l Conf. Pattern Recognition, pp. 638-641.
  26. Bensefia, A., Paquet, T., Heutte, L. (2005) “A Writer Identification and Verification System,” Pattern Recognition Letters, vol. 26, no. 10, pp. 2080-2092.
  27. Bensefia, A., Paquet, T., Heutte, L. (2005) Handwritten Document Analysis for Automatic Writer Recognition,” Electronic Letters on Computer Vision and Image Analysis, vol. 5, no. 2, pp. 72-86.
  28. Bensefia, A., Nosary, A., Paquet, T., Heutte, L. (2002) “Writer Identification by Writer’s Invariants,” Proc. Eighth Int’l Workshop Frontiers in Handwriting Recognition, pp. 274-279.
  29. Bensefia, A., Paquet, T., Heutte, L. (2003) “Information Retrieval Based Writer Identification,” Proc. Seventh Int’l Conf. Document Analysis and Recognition (ICDAR), pp. 946-950.
  30. Marti, U.V., Messerli, R., Bunke, H. (2001) “Writer Identification Using Text Line Based Features,” Proc. Sixth Int’l Conf. Document Analysis and Recognition (ICDAR), pp. 101-105.
  31. Hertel, C., Bunke, H. (2003) “A Set of Novel Features for Writer Identification,” Proc. Fourth Int’l Conf. Audio and Video-Based Biometric Person Authentication, pp. 679-687.
  32. Schlapbach, A., Kilchherr, V., Bunke, H. (2005) “Improving Writer Identification by Means of Feature Selection and Extraction,” Proc. Eighth Int’l Conf. Document Analysis and Recognition (ICDAR), pp. 131-135.
  33. Marti, U.V., Bunke, H. (2002) “The IAM-Database: An English Sentence Database for Offline Handwriting Recognition,” Int’l J. Document Analysis and Recognition, vol. 5, no. 1, pp. 39-46.
  34. Pervouchine, V., Leedham, G. (2007)Extraction and analysis of forensic document examiner features used for writer identification, Pattern Recognition Journal 40, 1004–1013.
  35. Schomaker, L., Franke, K., Bulacu, M. (2007) Using codebooks of fragmented connected-component contours in forensic and historic writer identification, Pattern RecognitionLetter28, 719–727.
  36. Schomaker, M.B.L. (2004) Analysis of texture and connected-component contours for the automatic identification of writers, in: 16th Belgium–Netherland Conference on Artificial Intelligence(BNAIC).
  37. Schlapbach, A., Bunke, H. (2007) A writer identification and verification system using HMM based recognizers, Pattern Analysis Application (Springer)10,33–43, doi:10.1007/s10044-006-0047-5.
  38. Schlapbach, A., Bunke, H. (2005) Writer identification using an HMM-based hand- writing recognition system: to normalize the input or not? In: 12th Conference of the International Graphonomics Society, Salerno, Italy, June 26–29, pp.138–142.
  39. Bulacu, M., Schomaker, L. (2006) Combining multiple features for text-independent writer identification and verification, in:10th international Workshop on Frontiers in Handwriting Recognition(IWFHR).
  40. Bulacu, M., Schomaker, L., Brink, A. (2007) Text-independent writer identification and verification on offline Arabic handwriting, in: Ninth Conference on Document Analysis and Recognition(ICDAR).
  41. Vander Maaten, L., Postma, E. ( 2005) Improving automatic writer identification, in:17thBelgium-Netherland Conference on Artificial Intelligence.
  42. Pervouchine, V., Leedham, G., Melikhov, K. (2005). Handwritten character skeletonisation for forensic document analysis, in: ACM Symposium on Applied Computing.
  43. Leeham, G., Chachra, S. (2003) Writer identification using innovative binarised features of handwriting numerals, in: Seventh International Conference on Document Analysis and Recognition (ICDAR).
  44. Al-Ma’adeed, S., Mohammed, E., AlKassis, D., Al-Muslih, F. (2008) Writer identification using edge-based directional probability distribution features for Arabic words, in: IEEE/ACS International Conference on Computer Systems and Applications (AICCSA), 582—590.
  45. Bulacu, M., Schomaker, L.(2007) Text-independent writer identification and verification using textural and allographic features, IEEE Transactions on Pattern Analysis and Machine Intelligence(PAMI)29(4) 701–717 Special Issue—Biometrics: Progress and Directions.
  46. Bulacu, M., Schomaker, L., Vuurpijl, L. (2003) Writer identification using edge-based directional features, in: Seventh International Conference on Document Analysis and Recognition (ICDAR).
  47. Al-Dmour, A., Zitar, R.A. (2007) Arabic writer identification based on hybrid spectral- statistical measures, Journal of Experimental & Theoretical Artificial Intelligence 19(4) 307–332.
  48. Feddaoui, N., Hamrouni, K. (2007). Personal Identification based on Texture Analysis of Arabic Handwriting Text.In: IEEE International Conference on Information and Communications Technologies (ICTTA’06), vol. (1), 1302-1307.
  49. Gazzah, S., Ben Amara, N. E. (2007). Arabic Handwriting Texture Analysis for Writer Identification using the DWT-lifting Scheme. In: 9th International Conference on Document Analysis and Recognition (ICDAR’07), vol. (2), 1133-1137.
  50. Abdi, M. N., Khemakhem, M., Ben-Abdallah, H. (2009) A Novel Approach for Off-Line Arabic Writer Identification Based on Stroke Feature Combination. In: 24th IEEE International Symposium on Computer and Information Sciences, (ISCIS’09).
  51. Shahabi, F., Rahmati, M. (2006) Comparison of Gabor-based features for writer identification of Farsi/Arabic handwriting, in: 10th International Workshop on Frontiers in Handwritten Recognition (IWFHR).
  52. Helli, B., Moghaddam, M.E. (2008) Persian writer identification using extended Gabor filter, in: International Conference on Image Analysis and Recognition (ICIAR).
  53. Helli, B., Moghaddam, M.E. (2008) A text-independent Persian writer identification system using LCS based classifier, in: IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2008.
  54. Helli, B., Moghaddam, M.E. (2009) A writer identification method based on XGabor and LCS, IEICE Electronics Express 6 (10).
  55. Ram, S.S., Moghaddam, M.E. (2009) Text-independent Persian writer identi- fication using fuzzy clustering approach, in: International Con- ference on Information Management and Engineering (ICIME), Malaysia.
  56. Ram, S.S., Moghaddam, M.E. (2009) A Persian writer identification method based on gradient features and neural networks, in: Second International Conference on Image and Signal Processing (CISP), China.
  57. Soleymani Baghshah, M., Bagheri Shouraki, S. Kasaei, S. (2006) A novel fuzzy classifier using fuzzy LVQ to recognize online Persian handwriting, in: Second IEEE Conference on Information and Communication Technology (ICTTA).
  58. Rafiee, A., Motavalli, H. (2007). Off-Line Writer Recognition for Farsi text. In: 6th Mexican International Conference on Artificial Intelligence (MICAI’07), Special Session, 193--197.
  59. Srihari, S. N., Cha, S.-H., Lee, S. (2001) “Establishing Handwriting Individuality Using Pattern Recognition Techniques," in Proceedings of the Sixth International Conference on Document Analysis and Recognition, pp. 1195-1204.
  60. Long Zuo, Yunhong Wang, Tieniu Tan, (2002).Personal Handwriting Identification Based on PCA, Proceedings of SPIE Second International Conference on Image and Graphics, pp 766-771.
  61. Pitak, T., Matsuura, T. (2004) On-line writer recognition for Thai based on velocity of barycenter of pen-point movement, in: International Conference on Image Processing, ICIP `04, vol. 2, pp. 889–892.
  62. Chan, S. K., Viard-Gaudin, C., Tay, Y. H. (2008)"Online writer identification using character prototypes distributions," inProceedings of SPIE - The International Society for Optical Engineering.
  63. Bulacu, M. Schomaker, L. (2003) “Writer Style from Oriented Edge Fragments,” Proc. 10th Int’l Conf. Computer Analysis of Images and Patterns, pp. 460-469.
  64. Schomaker, L., Bulacu, M., Franke, K. (2004) “Automatic Writer Identification Using Fragmented Connected-Component Contours,” Proc. Ninth Int’l Workshop Frontiers in Handwriting Recognition (IWFHR), pp. 185-190.
  65. Bulacu, M., Schomaker, L. (2005) “A Comparison of Clustering Methods for Writer Identification and Verification,” Proc. Eighth Int’l Conf. Document Analysis and Recognition, vol. II, pp. 1275-1279.
  66. Guo Xian Tan Christian. Automatic Writer Identification Framework for Online Handwritten Documents Using Character Prototypes
  67. Niels, R., Gootjen, F. Vuurpijl, L. (2008) "Writer Identification through Information Retrieval: The Allograph Weight Vector," in International Conference on Frontiers in Handwriting Recognition, pp. 481-486.
  68. Sutanto, P.,Leedham, G., Pervouchine, V. (2003) “Study of the consistency of some discriminatory features used by document examiners in the analysis of handwritten letter ’a’,” in International Conference on Document Analysis and Recognition, pp. 1091–1095.
  69. Pervouchine, V., Leedham, G. (2006) “Extraction and analysis of document examiner features from vector skeletons of grapheme ’th’,” in Document Analysis Systems, pp. 196–207.
  70. Xianliang, X. D., Wang, Liu, H. (2003) “Writer identification using directional element features and linear transform,” in International Conference on Document Analysis and Recognition.
  71. Tan, T. N. (1992) “Texture feature extraction via visual cortical channel modeling,” in International Conference of Pattern Recognition, vol. 3, pp. 607–610.
  72. Zhenyu, T. Y., He, Xinge, Y. (2005).A contourlet-based method for writer identification, International Conference on Systems, Man and Cybernetics, vol. 1, pp. 364–368.
  73. He, J. Y. Z., Fang, B., You, X. (2005) “A novel method for off-line handwriting-based writer identification,” in International Conference on Document Analysis and Recognition, pp. 242–256.
  74. Schomaker, L. Bulacu. (2004)Automatic writer identification using connected component contours and edge-based features of uppercase western script, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, pp. 787–798.
  75. Seropian, A., Grimaldi, M., Vincent, N. (2003) “Writer identification based on the fractal construction of a reference base,” in International Conference of Document Analysis and Recognition, pp. 1163–1167.
  76. Arazi, B. (1977).Handwriting identification by means of run-length measurements, IEEE Transactions of System, Man and Cybernatics, vol. 7, pp. 878–881.
  77. Arazi, B. (1983) “Automatic handwriting identification based on the external properties of the samples,” IEEE Transactions of System, Man and Cybernatics, vol. 13, pp. 635–642.
  78. Zimmerman, K., Varady, M. (1985) Hand writer identification from one-bit quantized pressure patterns, Pattern Recognition, vol. 18, no. 1, pp. 63–72.
  79. Nakamura, Y. Kidode, M. (2005) “Individuality analysis of online kanji handwriting,” in International Conference on Document Analysis and Recognition.
  80. Namboodiri, A.M., Gupta, S. (2006) “Text independent writer identification from online handwriting,”in Proceedings of 10th International Workshop on Frontiers in Handwriting Recognition, (La Baule, Centre de Congreee Atlantia, France), pp. 23–26.
  81. Jin, W., Wang, Y., Tan, T. (2005) “Text-independent writer identification based on fusion of dynamic and static features,” in International Workshop Biometric Recognition Systems, p. 197.
  82. Schlapbach, A. L., Marcus, Bunke, H. (2008).A writer identification system for on-line whiteboard data, Pattern Recognition Journal, 41, 23821–23897.
  83. Seiichiro Hangai, S. Y., Hamamoto, T. (2000) On-line signature verification based on altitude and direction of pen movement, vol. 1, pp. 489–492.
  84. Thumwarin, P., Matsuura, T. (2004) “On-line writer recognition for Thai based on velocity of barycenter of pen-point movement,” in IEEE International Conference on Image Processing, vol. Singapore, pp. 889–892, October 24-27.
  85. Tsai, L. M. Y. (2005) “Online writer identification using the point distribution model,” in International Conference on System, Man and Cybernetics, vol. 2, pp. 1264–1268.
  86. Hiroshi Kameya, S.M., Oka, R. (2003) “Figure-based writer verification by matching between an arbitrary part of registered sequence and an input sequence extracted from on-line handwritten figures,” in International Conference on Document Analysis and Recognition,
  87. Chapran, J. (2006).Biometric writer identification: feature analysis and classification, International JournalofPatternRecognitionandArtificialIntelligence20 (4), 483–503.
  88. Chapran, J., Fairhurst, M.C.( 2006) Biometric writer identification based on the interdependency between static and dynamic features of handwriting, in: Proceedings of the 10th International Workshop on Frontiers in Handwriting Recognition, pp. 505–510.
  89. Schlapbach, A., Bunke, H. (2004) Using HMM based recognizers for writer identification and verification, in: Proceedings–International Workshop on Frontiers in Handwriting Recognition, IWFHR, Tokyo, pp. 167–172.
Index Terms

Computer Science
Information Sciences

Keywords

Feature extraction online and offline schemes text independent text dependent Writer identification

Powered by PhDFocusTM