Robust text line segmentation for historical manuscript images using color and texture

Proceedings - International Conference on Pattern Recognition

Volumn , Issue , 2014, Pages 2978-2983

  Chen, Kai ^a   Wei, Hao ^a   Liwicki, Marcus ^a,b   Hennebert, Jean ^a,c   Ingold, Rolf ^a  

^a UNIVERSITY OF FRIBOURG   (Switzerland)

^b GERMAN RESEARCH CENTER FOR ARTIFICIAL INTELLIGENCE DFKI   (Germany)

^c UNIVERSITY OF APPLIED SCIENCES AND ARTS NORTHWESTERN SWITZERLAND   (Switzerland)

Author keywords

Document Understanding; Features and descriptors; Segmentation; Texture and color analysis

Indexed keywords

COLOR; COLOR IMAGE PROCESSING; HISTORY; PATTERN RECOGNITION; TEXTURES;

COLOR ANALYSIS; COLOR AND TEXTURE FEATURES; DESCRIPTORS; DOCUMENT UNDERSTANDING; FEATURE SELECTION ALGORITHM; LOCAL BINARY PATTERNS; POST-PROCESSING PROCEDURE; TEXT LINE SEGMENTATION;

IMAGE SEGMENTATION;

EID: 84919946888     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.2014.514     Document Type: Conference Paper

References (22)

1. T. Ahonen, A. Hadid, and M. Pietikäinen, Face Description with Local Binary Patterns: Application to Face Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 28, issue. 12, 2006, pp. 2037-2041.
2. A. Antonacopoulos and D. Karatzas, Document Image Analysis for World War II Personal Records, First International Workshop on Document Image Analysis for Libraries (DIAL), 2004, pp. 336-341.
3. M. Baechler and R. Ingold, Multi Resolution Layout Analysis of Medieval Manuscripts Using Dynamic MLP, Proceedings of The Eleventh International Conference on Document Analysis and Recognition, 2011, pp. 1185-1189.
4. I. Bar-Yosef, N. Hagbi, K. Kedem, and I. Dinstein, Line Segmentation for Degraded Handwritten Historical Documents, Internal Conference on Document Analysis and Recognition, 2009, pp. 1161-1165.
5. C.-C. Chang and C.-J. Lin, LIBSVM: A library for support vector machines, ACM Transactions on Intelligent Systems and Technology, 2011, vol. 2, issue 3, pp. 2:27:1-27:27.
6. A. Fischer, A. Keller, V. Frinken, and H. Bunke, Lexicon-Free Handwritten Word Spotting Using Character HMMs, Pattern Recognition Letters, vol. 33(7), 2012, pp. 934-942.
7. M. Hangarge, K. C. Santosh, S. Doddamani, and R. Pardeshi, Statistical Texture Features based Handwritten and Printed Text Classification in South Indian Documents, CoRR, abs/1303. 3087, 2013.
8. Y. He, N. Sang, and R. Huang, Local Binary Pattern histogram based Texton learning for texture classification, Image Processing (ICIP), 2011, 18th IEEE International Conference, pp. 145-153.
9. P. Hu, Y. Zhao, Z. Yang, and J. Wang, Recognition of gray character using gabor filters, Proceedings of the Fifth International Conference on Information Fusion, vol. 1, 2002, pp. 419-424.
10. Y. Li, Y. Zheng, D. Doermann, and S. Jaeger, Script-Independent Text Line Segmentation in Freestyle Handwritten Documents, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, no. 8, 2008, pp. 1313-1329.
11. A. Kitadai, J. Ishikawa, M. Nakagawa, M. Baba, and H. Watanabe, Document Image Retrieval to Support Reading Mokkans, The Eighth IAPR International Workshop on Document Analysis Systems, 2008, pp. 533-538.
12. F. Le Bourgeois and H. Emptoz, DEBORA: Digital AccEss to BOoks of the RenAissance, International Journal of Document Analysis and Recognition (IJDAR), vol. 9, issue 2-4, 2007, pp. 193-221.
13. L. Likforman-Sulem, A. Zahour, and B. Taconet, Text line segmentation of historical documents: A survey, International Journal of Document Analysis and Recognition (IJDAR), vol. 9, issue 2-4, 2007, pp. 123-138.
14. G. Louloudis, B. Gatos, I. Pratikakis, and C. Halatsis, Text Line and Word Segmentation of Handwritten Documents, Pattern Recognition, vol. 42, issue 12, 2009, pp. 3169-3183.
15. M. Seuret, Printed Content & Handwritten Notes Discrimination in Scanned Documents, Master Project, University of Fribourg, Department of Informatics, 2013.
16. T. Ojala, M. Pietikäinen, and T. Maenpaa, A Comparative Study of Texture Measures with Classification Based on Feature Distributions, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, issue. 7, 2002, pp. 971-987.
17. J. R. Quinlan, Induction of decision trees, Machine Learning, vol. 1, issue 1, 1986, pp. 81-106.
18. J. Y. Ramel, S. Busson, and M. L. Demonet, AGORA: the Interactive Document Image Analysis Tool of the BVH Project, Proceedings of the Second International Conference on Document Image Analysis for Libraries (DIAL), 2006, pp. 145-155.
19. H. Wei, M. Baechler, F. Slimane, and R. Ingold, Evaluation of SVM, MLP and GMM Classifiers for Layout Analysis of Historical Documents, International Conference on Document Analysis and Recognition (ICDAR), 2013, pp. 1220-1224.
20. F. Yin and C. L. Liu, Handwritten Chinese text line segmentation by clustering with distance metric learning, Pattern Recognition, vol. 42, issue 12, 2009, pp. 31463157.
21. L. Yu and H. Liu, Feature selection for high-dimensional data: A fast correlation-based filter solution, Proceedings of the Twentieth International Conference on Machine Learning, AAAI Press, 2003, pp. 856-863.
22. G. Zhao and M. Pietikäinen, Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, issue. 6, 2007, pp. 915-928.