Title :
Page Segmentation Based on Steerable Pyramid Features
Author :
Benjelil, M. ; Mullot, Remy ; Alimi, Adel M.
Author_Institution :
REGIM, ENIS, Sfax, Tunisia
Abstract :
Page segmentation and classification is very important in document layout analysis system before it is presented to an OCR system or for any other subsequent processing steps. In this paper, we propose an accurate and suitably 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 (either machine printed or handwritten) and non-text (images, graphics, drawings or paintings) in some noise-infected, deformed, multilingual, multi-script document images. These documents contain tabular structures, logos, stamps, handwritten script blocks, photos etc. The encouraging and promising results obtained on 1,000 official complex document images data set are presented in this research paper.
Keywords :
document image processing; feature extraction; image classification; image segmentation; optical character recognition; text analysis; transforms; OCR system; complex document images data set; complex documents segmentation; deformed document images; document layout analysis system; feature extraction; handwritten script blocks; handwritten text; logos; machine printed text; multilingual document images; multiscript document images; noise-infected document images; page classification; page segmentation; photos; pyramid subbands; stamps; steerable pyramid features; steerable pyramid transform; tabular structures; Band pass filters; Feature extraction; Graphics; Image decomposition; Image segmentation; Maximum likelihood detection; Measurement; Page segmenation; classification; pyramid features;
Conference_Titel :
Frontiers in Handwriting Recognition (ICFHR), 2012 International Conference on
Conference_Location :
Bari
Print_ISBN :
978-1-4673-2262-1
DOI :
10.1109/ICFHR.2012.253
