A hybrid method for three segmentation level of handwritten Arabic script

Authors:
Fadoua Bouafif Samoud;Samia Snoussi Maddouri;Noureddine Ellouze
Affiliations:
National School of Engineers of Tunis (ENIT);Signal, Image and Pattern recognition Lab (ENIT);National School of Engineers of Tunis (ENIT)
Venue:
Proceedings of the International Workshop on Multilingual OCR
Year:
2009

Citing 9
Cited 0

A new segmentation technique for omnifont Farsi text

Pattern Recognition Letters
A Hough based algorithm for extracting text lines in handwritten documents

ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 2) - Volume 2
Combination of Local and Global Vision Modelling for Arabic Handwritten Words Recognition

IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
Off-Line Handwritten Arabic Character Segmentation Algorithm: ACSA

IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
Arabic Hand-Written Text-Line Extraction

ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Recognising handwritten Arabic manuscripts using a single hidden Markov model

Pattern Recognition Letters
Automatic Segmentation and Recognition System for Handwritten Dates on Canadian Bank Cheques

ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
Word separation in handwritten legal amounts on bank cheques based on spatial gap distances

IEA/AIE'2004 Proceedings of the 17th international conference on Innovations in applied artificial intelligence
Text line segmentation of historical documents: a survey

International Journal on Document Analysis and Recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

The main theme of this paper is the segmentation of handwritten Arabic script into blocks, connected components and characters using a combination between Hough Transform and Mathematical Morphology tools. We start by a segmentation methodology of a complex document into its distinct entities namely handwritten components. Every extracted handwritten blocks are then segmented into sub-words as a main specificity of Arabic script. Finally a character segmentation method is presented. For each segmentation step, some concepts are needed such as dynamic kernel and Harris corner detectors. The proposed method is tested on the CENPARMI Arabic check database. We present a concept for automatic evaluation of the results, based on label tools for the different parts of used documents.