DocumentCode :
2022090
Title :
Locating Charts from Scanned Document Pages
Author :
Huang, Weihua ; Tan, Chew Lim
Author_Institution :
Nat. Univ. of Singapore, Singapore
Volume :
1
fYear :
2007
fDate :
23-26 Sept. 2007
Firstpage :
307
Lastpage :
311
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 non- chart 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 sub- goal, 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.
Keywords :
document image processing; image recognition; text analysis; chart image recognition; figure blocks; logical block labelling; scanned document pages; text blocks; text descriptions; understanding system; Graphics; Hidden Markov models; Image databases; Image recognition; Image segmentation; Labeling; Layout; Spatial databases; System testing; Text analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition, 2007. ICDAR 2007. Ninth International Conference on
Conference_Location :
Parana
ISSN :
1520-5363
Print_ISBN :
978-0-7695-2822-9
Type :
conf
DOI :
10.1109/ICDAR.2007.4378722
Filename :
4378722
Link To Document :
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