Offline recognition of omnifont Arabic text using the HMM ToolKit (HTK)

Authors:
M. S. Khorsheed
Affiliations:
King AbdulAziz City for Science and Technology (KACST), P.O. Box 6086, Riyadh 11442, Saudi Arabia
Venue:
Pattern Recognition Letters
Year:
2007

Citing 10
Cited 7

Recognition of handwritten word: first and second order hidden Markov model based approach

Pattern Recognition
Fundamentals of speech recognition

Fundamentals of speech recognition
Handwritten Word Recognition Using Segmentation-Free Hidden Markov Modeling and Segmentation-Based Dynamic Programming Techniques

IEEE Transactions on Pattern Analysis and Machine Intelligence
An Omnifont Open-Vocabulary OCR System for English and Arabic

IEEE Transactions on Pattern Analysis and Machine Intelligence
An HMM-Based Approach for Off-Line Unconstrained Handwritten Word Modeling and Recognition

IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognition of Off-Line Handwritten Arabic Words Using Hidden Markov Model Approach

ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Planar Markov Modeling for Arabic Writing Recognition: Advancement State

ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Multi-Font Arabic Word Recognition Using Spectral Features

ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Recognising handwritten Arabic manuscripts using a single hidden Markov model

Pattern Recognition Letters
Off-line recognition of handwritten Korean and alphanumeric characters using hidden Markov models

Pattern Recognition

Developing typewritten Arabic corpus with multi-fonts (TRACOM)

Proceedings of the International Workshop on Multilingual OCR
New features using fractal multi-dimensions for generalized Arabic font recognition

Pattern Recognition Letters
Comparison of global and cascading recognition systems applied to multi-font arabic text

Proceedings of the 10th ACM symposium on Document engineering
Performance of hidden Markov model and dynamic Bayesian network classifiers on handwritten Arabic word recognition

Knowledge-Based Systems
A markovian engine for text recognition: cursive arabic text, statistical features and interconnected HMMs

ICIAR'12 Proceedings of the 9th international conference on Image Analysis and Recognition - Volume Part I
A study on font-family and font-size recognition applied to Arabic word images at ultra-low resolution

Pattern Recognition Letters
Offline arabic handwritten text recognition: A Survey

ACM Computing Surveys (CSUR)

Quantified Score

Hi-index	0.10

Visualization

Abstract

This paper presents a cursive Arabic text recognition system. The system decomposes the document image into text line images and extracts a set of simple statistical features from a narrow window which is sliding a long that text line. It then injects the resulting feature vectors to the Hidden Markov Model Toolkit (HTK). HTK is a portable toolkit for speech recognition system. The proposed system is applied to a data corpus which includes Arabic text of more than 600 A4-size sheets typewritten in multiple computer-generated fonts.