DocumentCode :
2015413
Title :
An Approach for Multifont Arabic Characters Features Extraction Based on Contourlet Transform
Author :
Ben Amor, Nahla ; Ben Amara, Najoua Essoukri
Author_Institution :
Nat. Eng. Sch. of Tunis, Tunis
Volume :
2
fYear :
2007
fDate :
23-26 Sept. 2007
Firstpage :
1048
Lastpage :
1052
Abstract :
In this paper, we propose a method for features extraction from multifont Arabic characters images based on the Contourlet Transform, which has been recently introduced. In our previous works, we noticed that Wavelet transforms are not capable of reconstructing curved images perfectly; the Contourlet Transform offers a solution to remedy to this insufficiency. It allows a multiresolution and directional decomposition of a signal using a combination of Laplacian Pyramid (LP) and a Directional Filter Bank (DFB). The Contourlet Transform has good approximation properties for smooth 2D functions and finds a direct discrete-space construction, and is therefore computationally efficient. Experimental tests have been carried out on a set of 175.000 samples of characters corresponding to 9 different Arabic fonts. Some promising experimental results are reported.
Keywords :
character recognition; feature extraction; filtering theory; function approximation; image recognition; image reconstruction; image resolution; natural languages; transforms; Laplacian pyramid; contourlet transform; direct discrete-space construction; directional filter bank; feature extraction; function approximation; image reconstruction; image resolution; multifont Arabic character image recognition; signal decomposition; wavelet transform; Character recognition; Continuous wavelet transforms; Discrete transforms; Discrete wavelet transforms; Feature extraction; Filter bank; Fourier transforms; Image edge detection; Optical character recognition software; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition, 2007. ICDAR 2007. Ninth International Conference on
Conference_Location :
Parana
ISSN :
1520-5363
Print_ISBN :
978-0-7695-2822-9
Type :
conf
DOI :
10.1109/ICDAR.2007.4377075
Filename :
4377075
Link To Document :
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