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In this paper, we present a segmentation method of handwritten Arabic texts. The proposed method uses the algorithm for construction of the Outer Isothetic Cover (OIC) of a digital object. This technique 3allows the construction of polygons of all connected components on the binary image of the document. The first specificity of this method is that it allows the extraction of the shape of the script...
The identification of scripts is an important step in the characters recognition. In this work, we are interested in Arabic and Latin scripts. The identification is based on an approach to character recognition. The approach is structural feature. Selected characteristics of scripts are based on the geometric shape of the characters. Evaluations are conducted on a printed document Arabic and Latin,...
We present in this paper two hybrid segmentation methods of handwritten Arabic script. Both methods allow the segmentation of Arabic document in text lines and the segmentation of the text line into Pieces of Arabic Words (PAWs) respectively. The particularity of these two methods is that both use a combination with Mathematical Morphology (MM). The first method uses the (MM) in the first hand and...
This paper presents three evaluation criteria's for a comparison of two characters segmentation methods for handwritten Arabic words. The first segmentation method is based on a combination between the projection and the minima and maxima of the contour of the image. The second method is a combination between Hough Transform (HT) and Mathematical Morphology (MM) operators. These methods are developed,...
An important task in machine learning is the electronic reading of documents. In this process, discrimination between languages is one of the first steps in the problem of automatic document text recognition. We are interested in the processing of mixed Arabic/Latin printed documents. Our method is based essentially on the extraction of words. We first extract structural features of words and then...
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