Call For Paper Volume:4 Issue:8 Aug'2017 |

Arabic Handwritten Recognition using Hybrid Transform

Publication Date : 04/09/2015



Author(s) :

Dr. Anmar. A. RAZZAK , Mrs. Inaam Salman Aboud.


Volume/Issue :
Volume 2
,
Issue 9
(09 - 2015)



Abstract :

Automatic analysis of handwritten scripts is rapidly becoming an area of intense interest in computer vision and artificial intelligence research communities. In this paper an approach is presented for Arabic handwritten recognition of 58 Arabic characters including the beginning characters, ending characters and some of middle characters. The approach utilizes the hybrid transform in which consists of two transforms; the Wavelet transform and the discrete cosine transform (DCT). The approach suggested includes many steps such as preprocessing, feature extraction and clustering. In feature extraction phase the Wavelet transform and the discrete cosine transform (DCT) were implemented, in the clustering phase the Self Organizing Feature Map (SOFM) produced by Kohonen was implanted. Topological ordering patterns produced by Kohonen Self Organizing Feature Map, in which implemented on feature extracted for each of 58 Arabic characters used. The map will compute the topological relationship between the particular hand written character feature. The method tested using a new comprehensive Database of hand-written Arabic Words, Numbers, and Signatures.


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Arabic Handwritten Recognition using Hybrid Transform

September 4, 2015