DocumentCode :
969740
Title :
Table detection in online ink notes
Author :
Zhouchen Lin ; Junfeng He ; Zhicheng Zhong ; Rongrong Wang ; Heung-Yeung Shum
Author_Institution :
Microsoft Res. Asia, Beijing
Volume :
28
Issue :
8
fYear :
2006
Firstpage :
1341
Lastpage :
1346
Abstract :
In documents, tables are important structured objects that present statistical and relational information. In this paper, we present a robust system which is capable of detecting tables from free style online ink notes and extracting their structure so that they can be further edited in multiple ways. First, the primitive structure of tables, i.e., candidates for ruling lines and table bounding boxes, are detected among drawing strokes. Second, the logical structure of tables is determined by normalizing the table skeletons, identifying the skeleton structure, and extracting the cell contents. The detection process is similar to a decision tree so that invalid candidates can be ruled out quickly. Experimental results suggest that our system is robust and accurate in dealing with tables having complex structure or drawn under complex situations
Keywords :
decision trees; document image processing; feature extraction; cell content extraction; complex structure; decision tree; drawing strokes; free style online ink notes; logical structure; relational information; robust system; ruling lines; skeleton structure identification; statistical information; structure extraction; structured objects; table bounding boxes; table detection; table skeletons; Data mining; Decision trees; Graphics; Handwriting recognition; Information analysis; Ink; Robustness; Skeleton; Text analysis; Table detection; document analysis; graphics recognition; handwriting recognition; pen-based computing.; table recognition; Algorithms; Artificial Intelligence; Automatic Data Processing; Computer Graphics; Documentation; Handwriting; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Online Systems; Pattern Recognition, Automated; Statistics as Topic; User-Computer Interface;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/TPAMI.2006.173
Filename :
1642667
Link To Document :
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