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Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 2
An Approach for Multifont Arabic Characters Features Extraction Based on Contourlet Transform
Curitiba, Parana, Brazil
September 23-September 26
ISBN: 0-7695-2822-8
N. Ben Amor, National Engineering School of Tunis, National Engineering School of Sousse
N. Ben Amara, National Engineering School of Tunis, National Engineering School of Sousse
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.
Citation:
N. Ben Amor, N. Ben Amara, "An Approach for Multifont Arabic Characters Features Extraction Based on Contourlet Transform," icdar, vol. 2, pp.1048-1052, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 2, 2007
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