Title :
Newspaper document analysis featuring connected line segmentation
Author :
Mitchell, Phillip E. ; Yan, Hong
Author_Institution :
Sch. of Electr. & Inf. Eng., Sydney Univ., NSW, Australia
fDate :
6/23/1905 12:00:00 AM
Abstract :
This paper presents an algorithm designed to segment and classify newspaper documents. A notable feature of this algorithm is the ability to detect lines in the document - including lines that are connected to other components. A bottom-up approach is used to segment the image into patterns, and then each pattern is classified into one of seven types. Complete regions are then formed from the classified patterns
Keywords :
document image processing; electronic publishing; feature extraction; image segmentation; pattern classification; bottom-up method; connected line segmentation; feature extraction; image classification; image segmentation; newspaper document analysis; Algorithm design and analysis; Australia; Data structures; Design engineering; Image segmentation; Information analysis; Merging; Pattern classification; Shape; Text analysis;
Conference_Titel :
Document Analysis and Recognition, 2001. Proceedings. Sixth International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7695-1263-1
DOI :
10.1109/ICDAR.2001.953971
