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http://dx.doi.org/10.9717/kmms.2016.19.11.1837

Table Structure Recognition in Images for Newspaper Reader Application for the Blind  

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)
Publication Information
Journal of Korea Multimedia Society / v.19, no.11, 2016 , pp. 1837-1851 More about this Journal
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
Table Structure Recognition; Image to Speech; Row and Column Detection; Information Access Rights for Blind People;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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