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Recently, several researches were carried on handwritten document analysis field thanks to the evolution of data capture technologies. For a given document, multiple components could be treated as text, signatures and graphics. In this study, we present a new framework for a Multilanguage online handwritten text analysis where both script identification and recognition are made. The proposed system...
The online writer identification is a required component in many applications of Computer vision and Pattern Recognition. The offline writer identification is more developed in literature due to the use of traditional system based on Image Processing. There is a lack of works done in the case of online writer identification. In this paper, we propose a novel method to text independent writer identification...
This paper proposes an automatic text-independent online Arabic writer identification system. The main contribution of our system is to explore the utility of Beta-elliptic model in features extraction for online writer identification, due to the rich output of Beta-elliptic model in terms of graphical, kinematical and biometrical data. The efficiency of the considered features has been evaluated...
In this paper we present a new approach of Arabic diacritics modeling. The developed algorithm represents a section of the features extraction module of an online Arabic handwriting recognition system based on explicit grapheme segmentation strategy. The algorithm consists in three stages: first the detection of diacritics using the dimensions and the positions of the isolated handwriting strokes...
Online Handwriting Recognition is still of interest with the big demand on the nomadic computers and the pen based interfaces. For the Arabic language, it is far to be claimed as a solved problem. This paper presents an online Arabic Handwriting Recognition System based on Hidden Markov Models (HMMs) and Multi Layer Perceptron Neural Networks (MLPNNs). The input signal is segmented to continuous strokes...
This paper deals with the improvement of an on-line Arabic handwriting modeling system based on graphemes segmentation. The presented strategy consists in the integration of off-line features to assimilate and take up the handwriting style variation in a multi-writer context. The main contribution of the presented work consists in making off-line fuzzy template for each on-line segmented graphemes...
Writer identification still remains as a challenge area in the field of off-line handwriting recognition because only an image of the handwriting is available. Consequently, some information on the dynamic of writing, which is valuable for identification of writer, is unavailable in the off-line approaches, contrary to the on-line approaches where temporal and spatial information for the handwriting...
The aim of this paper is to address the task of writer Identification of on-line handwriting. A new method for analytical on-line writer identification is proposed. However, although it is possible to measure the degree of handwriting irregularity thanks to the fractal dimension, the fractal analysis with a single exponent is not enough sufficient to characterize handwriting styles variation, instead,...
In recent years, fractal and multi-fractal analysis have been widely applied in many domains, especially in the field of image processing. In this direction we present in this paper a novel method for Arabic text-dependent writer identification based on fractal and multi-fractal features; thus, from the images of Arabic words, we calculate their fractal dimensions by using the “Box-counting” method,...
We present in this paper a new approach of online Arabic handwriting modeling based on the graphemes segmentation. This segmentation rests on the previous detection of baseline. It involves the detection of two types of topologically meaningful points: the backs of the valleys adjoining the baseline and the angular points. The stage of features extraction allows to model the shapes of segmented graphemes...
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