Abstract
This paper describes a method to extract words from table regions in document images. The proposed approach consists of two stages: cell detection and word extraction. In the cell detection module, a table frame is extracted first by analyzing connected components and then intersection points are detected by a method using masks in the table frame. We correct false intersections, and detect the location of the cells within the table. In the word extraction module, a text region in each cell is located by using the connected components information that was obtained during the cell extraction module, and segmented into text lines by using projection profiles. Finally we divide the segmented lines into words using gap clustering and special symbol detection. The method correctly included character components touching the table frame with words, so experimental results show that more than 99% of words were successfully extracted from table regions.
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Jeong, CB., Park, SC., Son, HJ., Kim, SH. (2005). Word Extraction from Table Regions in Document Images. In: Fox, E.A., Neuhold, E.J., Premsmit, P., Wuwongse, V. (eds) Digital Libraries: Implementing Strategies and Sharing Experiences. ICADL 2005. Lecture Notes in Computer Science, vol 3815. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11599517_25
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DOI: https://doi.org/10.1007/11599517_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30850-8
Online ISBN: 978-3-540-32291-7
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