DocumentCode :
591973
Title :
A Study of Handwritten Characters by Shape Descriptors: Doping Using the Freeman Code
Author :
Gmati, C. ; Haboubi, Sofiene ; Alaqeeli, A. ; Amiri, Hamid
Author_Institution :
ENIT, SITI Lab., Tunis-Belvedere, Tunisia
fYear :
2012
fDate :
18-20 Sept. 2012
Firstpage :
285
Lastpage :
290
Abstract :
In this paper, we present the role of shape descriptors in the off-line recognition process of handwritten isolated Arabic and Latin characters. We will give some statistical and structural shape descriptors and mention their performance. Then we will present an hybrid approach that uses structural shapes´ descriptors from a different angle in order to improve the recognition´s results from a statistical descriptor. We will therefore introduce the concept of doping aiming to raise the recognition rate.
Keywords :
handwritten character recognition; image coding; statistical analysis; Freeman code; handwritten character; handwritten isolated Arabic character; handwritten isolated Latin character; offline recognition process; statistical shape descriptor; structural shape descriptor; Doping; Encoding; Feature extraction; Gabor filters; Shape; Support vector machine classification; Vectors; doping; fourier descriptor; freeman code; shape descriptors; statistical approaches; structural approaches;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Frontiers in Handwriting Recognition (ICFHR), 2012 International Conference on
Conference_Location :
Bari
Print_ISBN :
978-1-4673-2262-1
Type :
conf
DOI :
10.1109/ICFHR.2012.170
Filename :
6424407
Link To Document :
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