Steerable Pyramid Based Complex Documents Images Segmentation

Author

Benjelil, Mohamed ; Kanoun, Slim ; Mullot, RéMy ; Alimi, Adel M.

Author_Institution

REGIM-ENIS, Sfax, Tunisia

fYear

2009

Firstpage

833

Lastpage

837

Abstract

In this paper, we propose an accurate and suitable designed system for complex documents segmentation. This system is based on steerable pyramid transform. The features extracted from pyramid sub bands serve to locate and classify regions into text and non text in some noise infected, deformed, multilingual, multi script document images. These documents contain tabular structures, logos, stamps, handwritten text blocks, photos etc. The encouraging and promising results obtained on 1000 official complex documents images data set are presented in this research paper.

Keywords

document image processing; feature extraction; image classification; image segmentation; text analysis; transforms; document image segmentation; feature extraction; multilingual multi script document image; steerable pyramid; steerable pyramid transform; text region classification; Data mining; Feature extraction; Image analysis; Image recognition; Image retrieval; Image segmentation; Large-scale systems; Smoothing methods; Streaming media; Text analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Document Analysis and Recognition, 2009. ICDAR '09. 10th International Conference on

Conference_Location

Barcelona

ISSN

1520-5363

Print_ISBN

978-1-4244-4500-4

Electronic_ISBN

1520-5363

Type

conf

DOI

10.1109/ICDAR.2009.288

Filename

5277524