Youssef Ouadid

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Papers by Youssef Ouadid

Comparison Between the Polarity Inference Approach and the Sentiment Fine Analysis Approach Using Tweets

Advanced Intelligent Systems for Sustainable Development (AI2SD’2020), 2022

Boundary Segmentation of Optic Disc in Fundus Images

2017 14th International Conference on Computer Graphics, Imaging and Visualization, 2017

Optic disc (OD) segmentation is an essential step for automated detection of various serious opht... more Optic disc (OD) segmentation is an essential step for automated detection of various serious ophthalmic pathologies related to diabetic retinopathy. Therefore, exudates detection is our major purpose, but we must extract the OD prior to the process because it appears with similar color, intensity and contrast to other characteristics of the retinal image. The retinal image consists of blood vessels that emerge from the OD. This paper presents a novel method for segmentation of the OD in retinal images. The methodology includes localization of OD center, followed by elimination of vascular structure using vesselness filter. Finally, an active contour model was applied to boundary OD segmentation. The results are compared with a ground truth image from the ophthalmologist. The source retinal image for performing this work is obtained from the publicly available DRIVE and MESSIDOR database. This method offers a successful segmentation of OD which may help in diagnosis of various retinal abnormalities.

Handwritten Tifinagh Character Recognition Through a Structural Approach

2017 14th International Conference on Computer Graphics, Imaging and Visualization, 2017

In this article, we present a handwritten Tifinagh character recognition system based on a struct... more In this article, we present a handwritten Tifinagh character recognition system based on a structural approach which is graphs. It is composed of three main steps: pre-processing, features extraction and classification. In the preprocessing step, RGB thresholds, Morphological operations, normalization and thinning are applied to remove unwanted information from the image. In the feature extraction step, corners are extracted using a proposed algorithm then represented by an adjacency matrix defining the graph. These graphs are classified using a spectral graph matching method. Experimental results are obtained using multiple databases of handwritten Tifinagh characters to test the effectiveness. The system shows good results in terms of accuracy.

Analysis Of Satisfaction Of Banque Populaire Customers Through Their Tweets

International Journal of Scientific & Technology Research, 2020

The Social networks are an excellent source of information, and extraction of opinion. Nowadays, ... more The Social networks are an excellent source of information, and extraction of opinion. Nowadays, the most of internet users are using these platforms in order to share their sentiments and opinions about the products or services. The exploitation of these opinions is fruitfully. In this work, we expose the problem of sentiment analysis in social networks by showing the multiple experiments made in this context on Tweets using the two important approaches of this domain, namely, the Lexicon-Based Approach and the Machine Learning Approach. Also we introduce an original approach which incorporates the semantics in the second approach using the WorldNet lexical database.

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Pattern Recognition by Graphs : Application to Printed Tifinagh Character

Writing is one of the most essential medium to communicate with people. This is why we created ch... more Writing is one of the most essential medium to communicate with people. This is why we created character recognition systems to facilitate man-machine interaction. Most methods of character recognition existing require lot of pre-processing. Based on the idea that any form is apprehended by the human perception, we present a structural approach to recognition of Tifinagh characters (alphabet used by the Amazighe, mainly Tuareg). After using pre-processing techniques, we uses graphs representation as a model for offline recognition of printed Tifinagh characters. This representation allows extracting the basic form of an independent letter and recognizes it. The proposed approach shows its effectiveness against problems such as size and orientation resulting performance gain, also in term of its speed.

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Tifinagh Character Recognition: A Survey

2018 International Conference on Computing Sciences and Engineering (ICCSE), 2018

Optical Character Recognition (OCR) is considered as one of the important tools that contributes ... more Optical Character Recognition (OCR) is considered as one of the important tools that contributes to the communication man-machine. It is the conversion process of printed or handwritten text images into machine-encoded text. Intensive research has been done and a large number of works have been published on this topic during the last few decades especially for Roman, Chinese and Arabic scripts. As for Amazigh scripts (Tifinagh), due to its recent integration into information systems, the number of works done on Tifinagh Character Recognition is not sufficient. A state-of-the-art survey about the works available in the area of OCR for Amazigh scripts would be of a great aid to the researchers. Hence, a sincere attempt is made in this article to discuss the advancements reported recently in the literature. This survey is organized into six major sections covering a general overview (an introduction) about OCR systems and their techniques, methodologies of feature-based OCR, properties...

Sequential Primitive Classifier Combination for Amazigh Alphabets OCR

The main difficulty in developing a successful Optical Character Recognition (OCR) system lies in... more The main difficulty in developing a successful Optical Character Recognition (OCR) system lies in the confusion between the characters. In the case of Amazigh writing (Tifinagh alphabets), some characters have similarities based on rotation or scale. Most of the researchers attempted to solve this problem by combining multiple descriptors and / or classifiers which increased the recognition rate, but at the expense of processing time that becomes more prohibitive. Thus, reducing the confusion of characters and their recognition times is the major challenge of OCR systems. In this paper, we present an off-line OCR system for Tifinagh characters. Using a proposed key point extraction algorithm, character skeleton is divided into several segments. The length and orientation of every segment are stored into a feature vector, then the relationship between these segments are represented by a graph in the form of an incidence matrix. Classification is done by searching for similarity betwe...

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Segmentation of Optic Disc from Fundus Images

2018 International Conference on Computing Sciences and Engineering (ICCSE), 2018

Handwritten tifinagh character recognition using simple geometric shapes and graphs

Indonesian Journal of Electrical Engineering and Computer Science, 2019

In this paper, a graph based handwritten Tifinagh character recognition system is presented. In p... more In this paper, a graph based handwritten Tifinagh character recognition system is presented. In preprocessing Zhang Suen algorithm is enhanced. In features extraction, a novel key point extraction algorithm is presented. Images are then represented by adjacency matrices defining graphs where nodes represent feature points extracted by a novel algorithm. These graphs are classified using a graph matching method. Experimental results are obtained using two databases to test the effectiveness. The system shows good results in terms of recognition rate.

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Tifinagh Printed Character Recognition through Structural Feature Extraction

International Journal of Computer Vision and Image Processing, 2016

In this paper a system for the recognition of printed Tifinagh characters is presented. It is div... more In this paper a system for the recognition of printed Tifinagh characters is presented. It is divided into three main steps: preprocessing, feature extraction, and classification. Image quality is enhanced through preprocessing which are: binarization, normalization and thinning. Then the image is given to a proposed structural feature extracting algorithm where the character is divided into several geometrically sample shapes which are segments, then transformed into an undirected graph with unique coordinate of all nodes. The character is classified by matching the graph of the character and its counterpart graph which is generated from the images in the IRCAM database using an efficient spectral graph matching algorithm. Experimental results and analysis are accomplished by the use of 3267 random characters to test the effectiveness. The system shows good results in term of accuracy and CPU time.

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Spectral Graph Matching for Printed Tifinagh Character

2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV), 2016

Optical Character Recognition is one of the most important tools that contributes to facilitate m... more Optical Character Recognition is one of the most important tools that contributes to facilitate man-machine interaction. In this paper, we present an optical Tifinagh character recognition system based on graph theory. After preprocessing, interest points are extracted using Harris corner detector. Based on these points, we constructed the graph model representation of Tifinagh characters. Classification is done by calculating the spectral properties of adjacency matrix that represent the degree of agreement between graphs. The system shows satisfying performance and robustness against noise and deformation. The proposed system is evaluated using IRCAM database (Royal Institute of Amazigh Culture) and recognition rate of 99.02% was obtained.

Document Image Converter to XML File, Case of Tifinagh

International Journal of Computer Applications, 2016

The document image converter is a necessity in our life for many reasons such as digitization of ... more The document image converter is a necessity in our life for many reasons such as digitization of data in paper to secure them and gain time by automating this task, on the other hand preserving the environment by maintaining trees the first source of paper, for that this works based in a bi-cubic method for physical structure analyze and a graphs models representation for the characters recognition to generate at the end a standard XML file that can be used to create file is realised (doc, pdf ,html…).

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Tifinagh Character Recognition using Harris Corner Detector and Graph Representation

International Journal of Computer Applications, 2016

In this article, a printed Tifinagh character recognition system is presented. It is composed of ... more In this article, a printed Tifinagh character recognition system is presented. It is composed of three main steps: pre-processing, features extraction and classification. In the pre-processing step, binarization, normalization and thinning are applied to enhance the quality of the image. In the feature extraction step, corners are extracted using Harris Corner Detection method then represented by graph. In the classification step, graphs are compared using a graph matching method. Experimental results are obtained using IRCAM database to test the effectiveness. The system shows good results in terms of accuracy.

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Search-Based Classification for Offline Tifinagh Alphabets Recognition

Advancements in Computer Vision Applications in Intelligent Systems and Multimedia Technologies, 2020

The main difficulty in developing a successful optical character recognition (OCR) system lies in... more The main difficulty in developing a successful optical character recognition (OCR) system lies in the confusion between the characters. In the case of Amazigh writing (Tifinagh alphabets), some characters have similarities based on rotation or scale. Most of the researchers attempted to solve this problem by combining multiple descriptors and / or classifiers which increased the recognition rate, but at the expense of processing time that becomes more prohibitive. Thus, reducing the confusion of characters and their recognition times is the major challenge of OCR systems. In this chapter, the authors present an off-line OCR system for Tifinagh characters.

Youssef Ouadid

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