DocumentCode
2521533
Title
Online recognition of multi-stroke handwritten Urdu characters
Author
Khan, Kamran Ullah ; Haider, Ihtesham
Author_Institution
DEE, PIEAS, Islamabad, Pakistan
fYear
2010
fDate
9-11 April 2010
Firstpage
284
Lastpage
290
Abstract
Character recognition has enjoyed a lot of research in the recent past. Good recognition systems are available commercially for alphabetical languages based on Roman characters and for symbolic languages like Chinese. But languages based on Arabic alphabets like Arabic, Urdu etc. do not have such recognition systems. The recognition systems generally have a scanner or camera as the input device for off-line recognition, or a stylus/tablet as input device for online recognition. These systems are used in conjunction with the input peripheral devices like keyboards and mice. With the recent developments in electronic tablets, pen movements can be captured more accurately. This paper presents part of the work for online recognition of handwritten Urdu language characters. Urdu language is based on Arabic alphabets with larger character set as compared to Arabic (37 characters). Urdu, due to its large character set and limited number strokes, is difficult to recognize. Many characters are similar with little differences. Online recognition of multi stroke (two-, three-, and four-stroke) handwritten Urdu characters is presented in this paper, whereas, single-stroke character recognition was presented in a preceding work. After necessary preprocessing, some novel features are extracted. Various types of classification methodologies are then tested in order to find the best combination of features and classifiers for two-, three-, and four-strokes handwritten Urdu characters recognition.
Keywords
cameras; feature extraction; handwritten character recognition; image scanners; keyboards; light pens; mouse controllers (computers); natural languages; Arabic alphabets; Roman characters; alphabetical languages; camera; character recognition; classifiers; electronic tablets; feature extraction; input peripheral devices; multi-stroke handwritten Urdu characters; off-line recognition; online recognition; pen movements; recognition systems; scanner; symbolic languages; Cameras; Character recognition; Feature extraction; Handwriting recognition; Keyboards; Mice; Natural languages; Neural networks; Testing; Writing; Back Propagation Neural Network; Correlation based Classifier; Major Stroke; Minor Stroke; Online Characters Recognition; Probabilistic Neural Network; Template Matching;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Analysis and Signal Processing (IASP), 2010 International Conference on
Conference_Location
Zhejiang
Print_ISBN
978-1-4244-5554-6
Electronic_ISBN
978-1-4244-5556-0
Type
conf
DOI
10.1109/IASP.2010.5476113
Filename
5476113
Link To Document