Geometric structure analysis of document images: a knowledge-based approach

Author

Lee, Kyong-Ho ; Choy, Yoon-Chul ; Cho, Sung-Bae

Author_Institution

Dept. of Comput. Sci., Yonsei Univ., Seoul, South Korea

Volume

22

Issue

11

fYear

2000

fDate

11/1/2000 12:00:00 AM

Firstpage

1224

Lastpage

1240

Abstract

This paper presents a knowledge-based method for sophisticated geometric structure analysis of technical journal pages. The proposed knowledge base encodes geometric characteristics that are not only common in technical journals but also publication-specific in the form of rules. The method takes the hybrid of top-down and bottom-up techniques and consists of two phases: region segmentation and identification. Generally, the result of the segmentation process does not have a one-to-one matching with composite layout components. Therefore, the proposed method identifies non-text objects, such as images, drawings, and tables, as well as text objects, by splitting or grouping segmented regions into composite layout components. Experimental results with 372 images scanned from the IEEE Transactions on Pattern Analysis and Machine Intelligence show that the proposed method has performed geometric structure analysis successfully on more than 99 percent of the test images.

Keywords

character recognition; computational geometry; document image processing; image matching; image segmentation; knowledge based systems; bottom-up method; document images; geometric structure analysis; image matching; knowledge-based systems; region identification; region segmentation; technical journal; top-down method; Equations; Humans; Image analysis; Image segmentation; Pattern analysis; Performance analysis; Performance evaluation; Testing; Text analysis; Transforms;

fLanguage

English

Journal_Title

Pattern Analysis and Machine Intelligence, IEEE Transactions on

Publisher

ieee

ISSN

0162-8828

Type

jour

DOI

10.1109/34.888708

Filename

888708