Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICDAR.2007.4378764
Title: Extraction of vectorized graphical information from scientific chart images
Authors: Liu, R. 
Huang, W. 
Chew, L.T. 
Issue Date: 2007
Source: Liu, R.,Huang, W.,Chew, L.T. (2007). Extraction of vectorized graphical information from scientific chart images. Proceedings of the International Conference on Document Analysis and Recognition, ICDAR 1 : 521-525. ScholarBank@NUS Repository. https://doi.org/10.1109/ICDAR.2007.4378764
Abstract: Graphical components information extraction is a crucial step in the chart recognition and understanding process. However, existing methods of information extraction from chart images either are type-dependent or rely on certain assumptions. In this paper, we present a general method to extract vectorized graphical information from scientific chart images. Our algorithm firstly constructs a data structure called directional single-connected chains (DSCC). It then employs ellipse-specific fitting and orthogonal diagonalization to calculate the curvatures of the chains and classify the chains into either straight lines or arcs. Finally we combine all straight lines and all arcs accordingly and use linear regression to compute their attributes. The DSCC has a good property in that it is less susceptible to noise. The experiment results show that our algorithm is efficient, robust and accurate. © 2007 IEEE.
Source Title: Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
URI: http://scholarbank.nus.edu.sg/handle/10635/40568
ISBN: 0769528228
ISSN: 15205363
DOI: 10.1109/ICDAR.2007.4378764
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