Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
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Table Structure Recognition in Images for Newspaper Reader Application for the Blind

시각 장애인용 신문 구독 프로그램을 위한 이미지에서 표 구조 인식

  • Kim, Jee Woong (School of Computer Science and Electrical Engineering, Handong Global University) ;
  • Yi, Kang (School of Computer Science and Electrical Engineering, Handong Global University) ;
  • Kim, Kyung-Mi (School of Global Leadership, Handong Global University)
  • Received : 2016.08.09
  • Accepted : 2016.11.02
  • Published : 2016.11.30
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Abstract

Newspaper reader mobile applications using text-to-speech (TTS) function enable blind people to read newspaper contents. But, tables cannot be easily read by the reader program because most of the tables are stored as images in the contents. Even though we try to use OCR (Optical character reader) programs to recognize letters from the table images, it cannot be simply applied to the table reading function because the table structure is unknown to the readers. Therefore, identification of exact location of each table cell that contains the text of the table is required beforehand. In this paper, we propose an efficient image processing algorithm to recognize all the cells in tables by identifying columns and rows in table images. From the cell location data provided by the table column and row identification algorithm, we can generate table structure information and table reading scenarios. Our experimental results with table images found commonly in newspapers show that our cell identification approach has 100% accuracy for simple black and white table images and about 99.7% accuracy for colored and complicated tables.

Keywords

References

  1. J. Lee, J. Lee, and S. Lim, "Implementation & Usability Evaluation of Math Expression Reader for Domestic Reading Disables," Journal of Korea Multimedia Society, Vol. 15, No. 7, pp. 951-961, July 2012. https://doi.org/10.9717/kmms.2012.15.7.951
  2. S. Kim, N. Hwang, H. Jeong, and K. Yi, "Design and Implementation of Mobile Newspaper Reader Application User Interface for Blind Persons," Proceedings of KI ISE Korea Computer Congress, pp. 1928-1930, 2014.
  3. S. Faisal and R. Smith, "Table Detection in Heterogeneous Documents," Proceedings of the 9th IAPR International Workshop on Document Analysis Systems, pp. 65-72, 2010.
  4. B. Gatos, D. Danatsas, I. Pratikakis and S. J. Perantonis, "Automatic Table Detection in Document Images," Proceeding of International Conference on Pattern Recognition and Image Analysis, pp. 609-618, 2005.
  5. C. Jin and D. Lopresti. "Model-based Tabular Structure Detection and Recognition in Noisy Handwritten Documents," Proceeding of Frontiers in Handwriting Recognition, pp. 75-80, 2012.
  6. J. Hu, R. Kashi, D. Lopresti, and G. Wilfong, "Table Structure Recognition and Its Evaluation," Proceeding of Photonics West 2001-Electronic Imaging International Society for Optics and Photonics, pp. 44-55, 2001.
  7. W.K. Seo, H.I. Koo, D.H. Lee. S.H. Kim, and N.I. Cho, "Table Recognition Algorithm for Camera-captured Document Images Based on Junction Detection and Labeling," Proceedings of The Korean Society of Broad Engineers, pp. 263-266, 2013.
  8. J. Jung, "Line Edge-Based Type-Specific Corner Points Extraction for the Analysis of Table Form Document Structure," Journal of Digital Contents Society, Vol. 15, No. 2, pp. 209-217, 2014. https://doi.org/10.9728/dcs.2014.15.2.209
  9. Amano, A., Asada, N., Mukunoki, M., & Aoyama, M., "Table form document analysis based on the document structure grammar," International Journal of Document Analysis and Recognition, Vol. 8.2-3, pp. 201-213, 2006. https://doi.org/10.1007/s10032-005-0008-3
  10. P. Blenkhorn and D.G. Evans, "Using Speech and Touch to Enable Blind People to Access Schematic Diagrams," Journal of Network and Computer Applications, Vol. 21, pp. 17-29, 1998. https://doi.org/10.1006/jnca.1998.0060

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