Please use this identifier to cite or link to this item: https://doi.org/10.1117/12.410854
Title: Hough-based model for recognizing bar charts in document images
Authors: Yan Ping Zhou
Chew Lim Tan 
Keywords: Document recognition
Graphics recognition
Hough Transform
Issue Date: 2001
Source: Yan Ping Zhou,Chew Lim Tan (2001). Hough-based model for recognizing bar charts in document images. Proceedings of SPIE - The International Society for Optical Engineering 4307 : 333-340. ScholarBank@NUS Repository. https://doi.org/10.1117/12.410854
Abstract: Bar charts are the most basic graphic representation for scientific data in technical and business papers. The objective of bar chart recognition in document image analysis is to extract graphics and text primitives structurally, then to correlate graphic interpretative information with text primitives semantically. This paper proposes a new model for generic bar chart recognition. We first change the image space into the hough space by applying Hough Transform on the feature points. Then we use hyphothesis-testing bar pattern searching algorithm to detect the bar patterns. We also apply a new text primitives grouping algorithm to extract text primitives. Finally, we interpret bar primitives by correlating them with corresponding text primitives like human's visual processing. The results show that the new model can recognize bar charts lying in any orientations, such as slant bar charts, or even hand-drawn bar charts.
Source Title: Proceedings of SPIE - The International Society for Optical Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/40479
ISSN: 0277786X
DOI: 10.1117/12.410854
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