Steerable Pyramid Based Complex Documents Images Segmentation

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.

• Type: Journal
• Year: 2009
• Where: ICDAR
• Authors: Mohamed Benjelil, Slim Kanoun, Rémy Mullot, Adel M. Alimi
• Keywords: Complex Documents, Complex Documents Segmentation, Document Analysis, Documents, ICDAR 2009