DocumentCode
3330992
Title
Page segmentation and classification using fast feature extraction and connectivity analysis
Author
Sauvola, Jaakko ; Pietikainen, Matti
Author_Institution
Dept. of Electr. Eng., Oulu Univ., Finland
Volume
2
fYear
1995
fDate
14-16 Aug 1995
Firstpage
1127
Abstract
Page segmentation and classification are important parts of the document analysis process. The aim is to extract and classify different parts of the page. This paper proposes an approach in which these two phases are combined. The integration process includes fast feature extraction with rule-based classification and label propagation using connectivity analysis providing classified areas in three categories: background, text and picture
Keywords
feature extraction; image classification; image segmentation; knowledge based systems; background; connectivity analysis; document analysis process; fast feature extraction; integration process; label propagation; page classification; page segmentation; picture; rule-based classification; text; Availability; Electronic mail; Feature extraction; Gabor filters; Government; Image segmentation; Optical character recognition software; Personal communication networks; Text analysis; Text recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Document Analysis and Recognition, 1995., Proceedings of the Third International Conference on
Conference_Location
Montreal, Que.
Print_ISBN
0-8186-7128-9
Type
conf
DOI
10.1109/ICDAR.1995.602118
Filename
602118
Link To Document