DocumentCode
396687
Title
Using artificial neural networks to identify headings in newspaper documents
Author
Zhang, Wei ; Andersen, Timothy L.
Author_Institution
Comput. Sci. Dept., Boise State Univ., ID, USA
Volume
3
fYear
2003
fDate
20-24 July 2003
Firstpage
2283
Abstract
Several features for Neural Network based document region identification are tested. Specifically, this paper examines features for headline and subheadline region identification. The Neural Network based region identification algorithm is a key component of a document recognition system that segments a document into regions, classifies them into text, graphic, photo, and other region types, and then uses this classification to guide the processing and analysis of the image. The input data are unusually challenging: low quality images of newspaper documents obtained from microfilmed archives. Experiments on several newspaper documents show that the features used are capable of robust and accurate headline identification.
Keywords
document image processing; learning (artificial intelligence); neural nets; pattern classification; artificial neural networks; document recognition system; headline region identification; image analysis; image processing; microfilm archives; newspaper documents; newspaper headings identification; subheadline region identification; Artificial neural networks; Graphics; Image analysis; Image recognition; Image segmentation; Intelligent networks; Optical character recognition software; Pixel; Text analysis; Text recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2003. Proceedings of the International Joint Conference on
ISSN
1098-7576
Print_ISBN
0-7803-7898-9
Type
conf
DOI
10.1109/IJCNN.2003.1223767
Filename
1223767
Link To Document