A new table interpretation methodology with little knowledge base: table interpretation methodology

ABSTRACT

In this paper, a new methodology for table-form interpretation with little previous knowledge is presented. The first module performs the identification of line intersections in a table-form, the second module detects and corrects wrong intersections produced by fault intersection segments or by table artefacts (smudges, overlapping of handwritten data and fault segments). The third module performs the table-form cell extraction. The features used to interpret the table-form are directly extracted from the image itself by means of morphological tools. The evaluation of the efficiency is carried out from a total of 305 table-form images. Experiments showed significant and promising results. The proposed approach reached a success rate over than 87% on average. The main advantage of the proposed methodology is requiring little knowledge from documents, being able to apply for a table-form majority.

REFERENCES

• 1: J. F. Arias , A. Chhabra , V. Misra, Interpreting and representing tabular documents, Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96), p.600, June 18-20, 1996
• 2: J. F. Arias , R. Kasturi , A. Chhabra, Efficient techniques for telephone company line drawing interpretation, Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 2), p.795, August 14-15, 1995
• 3: Bertrand Coüasnon, DMOS: A Generic Document Recognition Method, Application to an Automatic Generator of Musical Scores, Mathematical Formulae and Table Structures Recognition Systems, Proceedings of the Sixth International Conference on Document Analysis and Recognition, p.215, September 10-13, 2001
• 4: Kuo-Chin Fan , Jeng-Ming Lu , Liang-Sheng Wang , Hong-Yuan Liao, Extraction of characters from form documents by feature point clustering, Pattern Recognition Letters, v.16 n.9, p.963-970, Sept. 1995 [doi>10.1016/0167-8655(95)00040-N]
• 5: Field Extraction Method from Existing Forms Transmitted by Facsimile, Proceedings of the Sixth International Conference on Document Analysis and Recognition, p.738, September 10-13, 2001
• 6: O. Hori , D. S. Doermann, Robust table-form structure analysis based on box-driven reasoning, Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 1), p.218, August 14-15, 1995
• 7: J. Hu, R. S. Kashi, D. Lopresti, and G. T. Wilfong. Evaluating the performance of table processing algorithms. International Journal on Document Analysis and Recognition, 4:140--153, 2002.
• 8: Thomas Kieninger , Andreas Dengel, The T-Recs Table Recognition and Analysis System, Selected Papers from the Third IAPR Workshop on Document Analysis Systems: Theory and Practice, p.255-269, November 04-06, 1998
• 9: Jisheng Liang , Jaekyu Ha , Robert M. Haralick , Ihsin T. Phillips, Document Layout Structure Extraction Using Bounding Boxes of Different Entities, Proceedings of the 3rd IEEE Workshop on Applications of Computer Vision (WACV '96), p.278, December 02-04, 1996
• 10: L. A. P. Neves. Extraĉão de células de dados manuscritos em tabelas. Master's thesis, Pontifícia Universidade Católica do Paraná - PUCPR, 1999.
• 11: A. Pizano. Extracting line features from images of business forms and tables. IAPR - In: Proceedings of the 11th International Conference on Pattern Recognition, 3:399--403, 1992.
• 12: S. Shimotsuji , M. Asano, Form Identification Based on Cell Structure, Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276, p.793, August 25-29, 1996
• 13: A Recursive Analysis for Form Cell Recognition, Proceedings of the Sixth International Conference on Document Analysis and Recognition, p.694, September 10-13, 2001
• 14: R. T. V. Thom. Modlisation de Tableaux pour le traitement Automatique des Formulaires. Laboratoire PSI, Universit de Rouen, 1997.
• 15: J. W. Tukey. Exploratory Data Analysis. Addison-Wesley, 1977.
• 16: T. Watanabe, Q. Luo, and N. Sugie. A cooperative document understanding method among multiple recognition procedures. In: Proceedings of the 11th IAPR International Conference on Pattern Recognition Method Systems, pages 689--692, 1992.
• 17: T. Watanabe, Q. Luo, and N. Sugie. Structure recognition methods for various types of documents. Machine Vision and Applications, 1993.
• 18: T. Watanabe, Q. Luo, and N. Sugie. Toward a practical document understanding of table-form documents: Its framework and knowledge representation. In: Proceedings of the Second Conference on Document Analysis and Recognition, pages 510--515, 1993.
• 19: Toyohide Watanabe , Qin Luo , Noboru Sugie, Layout Recognition of Multi-Kinds of Table-Form Documents, IEEE Transactions on Pattern Analysis and Machine Intelligence, v.17 n.4, p.432-445, April 1995 [doi>10.1109/34.385976]

INDEX TERMS

Primary Classification:
  D. Software
  D.2 SOFTWARE ENGINEERING

General Terms:
Algorithms

Keywords:
document segmentation, handwritten data, table-form extraction, table-form recognition