Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICDAR.2007.4378722
Title: Locating charts from scanned document pages
Authors: Huang, W. 
Chew, L.T. 
Issue Date: 2007
Source: Huang, W.,Chew, L.T. (2007). Locating charts from scanned document pages. Proceedings of the International Conference on Document Analysis and Recognition, ICDAR 1 : 307-311. ScholarBank@NUS Repository. https://doi.org/10.1109/ICDAR.2007.4378722
Abstract: This paper presents our work on automatically locating charts from document pages, which is an important stage in our chart image recognition and understanding system currently being developed. To achieve this, there are two sub-goals to be reached: locating figure blocks in a given document image, and building a classifier to differentiate charts from nonchart figures. For the first sub-goal, besides traditional logical block labelling, relevant text blocks such as text descriptions and labels in a figure must be included in the located figure blocks to facilitate the interpretation processes in the following stages. For the second subgoal, we propose a set of simple statistical features for building the classifier. We tested our system with the entire collection of scanned journal pages in the University of Washington database I. The experimental results are discussed in this paper. © 2007 IEEE.
Source Title: Proceedings of the International Conference on Document Analysis and Recognition, ICDAR
URI: http://scholarbank.nus.edu.sg/handle/10635/41053
ISBN: 0769528228
ISSN: 15205363
DOI: 10.1109/ICDAR.2007.4378722
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