Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
International Journal on Document Analysis and Recognition (IJDAR)
Published in: International Journal on Document Analysis and Recognition (IJDAR) 4/2015

01-12-2015 | Original Paper

RETRACTED ARTICLE: Offline scripting-free author identification based on speeded-up robust features

Authors: Manoj Kumar Sharma, Vijay Pal Dhaka

Published in: International Journal on Document Analysis and Recognition (IJDAR) | Issue 4/2015

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

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.
previous article Handwritten word recognition using Web resources and recurrent neural networks
next article CERMINE: automatic extraction of structured metadata from scientific literature

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
Literature
1.
Zois, E., Anastassopoulos, V.: Morphological waveform coding for writer identification. Pattern Recognit. 33(3), 385–398 (2000)CrossRef
2.
Tan, T., Said, H., Baker, K.: Personal identification based on handwriting. Pattern Recognit. 33(1), 149–160 (2000)CrossRef
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)CrossRef
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)CrossRef
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)CrossRef
7.
Ryu, J.: Il Koo, H.: Language-independent text-line extraction algorithm for handwritten documents. IEEE Signal Process. Lett. 21(9), 1115–1119 (2014)CrossRef
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)CrossRef
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)CrossRef
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)CrossRef
11.
van der Zant, T.: Handwritten-word spotting using biologically inspired features. IEEE Trans. Pattern Anal. Mach. Intell. 30(11), 1945–1957 (2008)CrossRef
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)CrossRef
13.
Ghosh, D., Dube, T., Shivaprased, A.P.: Script recognition–a review. IEEE Trans. Pattern Anal. Mach. Intell. 32(12), 2142–2161 (2010)CrossRef
14.
Lowe, D.: Distinctive image features from scale-invariant key points. Int. J. Comput. Vis. 60(2), 91–110 (2004)CrossRef
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.
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)CrossRef
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)CrossRef
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)
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.
25.
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)
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)CrossRef
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)CrossRef
31.
Srihari, S., Cha, S., Arora, H., Lee, S.: Individuality of handwriting. J. Forensic Sci. 47(4), 856–872 (2002)CrossRef
32.
Gatos, B., Louloudis, G., Pratikakis, I., Halatsis, C.: Text line and word segmentation of handwritten documents. Pattern Recognit. 42(12), 3169–3183 (2009)CrossRef
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)CrossRef
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)CrossRef
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)CrossRef
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)CrossRef
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)CrossRef
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)CrossRef
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)CrossRef
Metadata
Title
RETRACTED ARTICLE: Offline scripting-free author identification based on speeded-up robust features
Authors
Manoj Kumar Sharma
Vijay Pal Dhaka
Publication date
01-12-2015
Publisher
Springer Berlin Heidelberg
Published in
International Journal on Document Analysis and Recognition (IJDAR) / Issue 4/2015
Print ISSN: 1433-2833
Electronic ISSN: 1433-2825
DOI
https://doi.org/10.1007/s10032-015-0252-0

Other articles of this Issue 4/2015

International Journal on Document Analysis and Recognition (IJDAR) 4/2015 Go to the issue

Original Paper

g-DICE: graph mining-based document information content exploitation

Original Paper

CERMINE: automatic extraction of structured metadata from scientific literature

Original Paper

Handwritten word recognition using Web resources and recurrent neural networks

Original Paper

Nastalique segmentation-based approach for Urdu OCR

Premium Partner

    Image Credits