Détail de l'auteur
Auteur Fella Hachouf |
Documents disponibles écrits par cet auteur (7)
Affiner la recherche Interroger des sources externes
Titre : Une approche hybride pour la segmentation d’images : Application aux images médicales Type de document : texte imprimé Auteurs : Nassima Mezhoud, Auteur ; Fella Hachouf, Directeur de thèse Editeur : Constantine : Université Mentouri Constantine Année de publication : 2012 Importance : 98 f. Format : 31 cm. Note générale : Doctorat en sciences
2 copies imprimées disponiblesLangues : Français (fre) Catégories : Français - Anglais
InformatiqueTags : Segmentation d’images images médicales méthode hybride réseau de neurones algorithmes génétiques espace couleur HSV Index. décimale : 004 Traitement de données. Informatique Diplôme : Doctorat en sciences En ligne : ../theses/informatique/MEZ6197.pdf Format de la ressource électronique : Permalink : https://bu.umc.edu.dz/md/index.php?lvl=notice_display&id=6170 Une approche hybride pour la segmentation d’images : Application aux images médicales [texte imprimé] / Nassima Mezhoud, Auteur ; Fella Hachouf, Directeur de thèse . - Constantine : Université Mentouri Constantine, 2012 . - 98 f. ; 31 cm.
Doctorat en sciences
2 copies imprimées disponibles
Langues : Français (fre)
Catégories : Français - Anglais
InformatiqueTags : Segmentation d’images images médicales méthode hybride réseau de neurones algorithmes génétiques espace couleur HSV Index. décimale : 004 Traitement de données. Informatique Diplôme : Doctorat en sciences En ligne : ../theses/informatique/MEZ6197.pdf Format de la ressource électronique : Permalink : https://bu.umc.edu.dz/md/index.php?lvl=notice_display&id=6170 Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité MEZ/6197 MEZ/6197 Thèse Bibliothèque principale Thèses Disponible
Titre : La classification dans les sous espaces pour l’analyse d’images Type de document : texte imprimé Auteurs : Amel Boulemnadjel, Auteur ; Fella Hachouf, Directeur de thèse Editeur : جامعة الإخوة منتوري قسنطينة Année de publication : 2016 Importance : 115 f. Format : 30 cm. Note générale : 2 copies imprimées disponibles
Langues : Français (fre) Catégories : Français - Anglais
ElectroniqueTags : clustering subspace SVM active learning 2D-RCA GMM Classification sous espace Apprentissage actif Index. décimale : 621 Electronique Résumé : "Clustering problem consists in partitioning a given data set into groups called clus¬ters, such that the data points in a cluster are more similar to each other than points in different clusters. The clustering in high-dimensional data is extremely difficult. In high dimensional datasets, the clusters can be characterized only by some dimensions subsets.
These relevant dimensions can be different from one cluster to another. A new challenging research field has emerged, namely the subspace clustering. It is an extension of traditio¬ nal clustering that seeks to find clusters in different subspaces within a dataset. Image processing and image analysis tools are widely used in different domains. However, exploi¬ ting these images is tightly dependant of their textures. In this work, we have developed
two approaches to image classification. The first one is a subspace clustering method. It is an iterative algorithm based on the minimization of an objective function. This function is formed by a separation and compactness terms. The cluster density is also introduced in the compactness term. An initialization step has been improved by a multi class SVM algorithm. An active learning with SVM is incorporated in the classification process to speed the proposed algorithm convergence. It allows enhancing the cluster center loca¬ tion. The second approach is based on a new non linear model which extends the random coefficients autoregressive model (RCA) to a bidimensionally RCA model (2D-RCA).The coefficients are estimated by the generalized moments method (GMM). It is a supervised method.
We have proposed different versions of classification algorithms. The developed approaches have been tested and evaluated on different synthetic datasets and textures and real images. Experimental results have corroborated the effectiveness of the proposed method compared to well-established and state-of-the-art methods.
Diplôme : Magistère En ligne : ../theses/electronique/BOU6972.pdf Format de la ressource électronique : Permalink : https://bu.umc.edu.dz/md/index.php?lvl=notice_display&id=10370 La classification dans les sous espaces pour l’analyse d’images [texte imprimé] / Amel Boulemnadjel, Auteur ; Fella Hachouf, Directeur de thèse . - جامعة الإخوة منتوري قسنطينة, 2016 . - 115 f. ; 30 cm.
2 copies imprimées disponibles
Langues : Français (fre)
Catégories : Français - Anglais
ElectroniqueTags : clustering subspace SVM active learning 2D-RCA GMM Classification sous espace Apprentissage actif Index. décimale : 621 Electronique Résumé : "Clustering problem consists in partitioning a given data set into groups called clus¬ters, such that the data points in a cluster are more similar to each other than points in different clusters. The clustering in high-dimensional data is extremely difficult. In high dimensional datasets, the clusters can be characterized only by some dimensions subsets.
These relevant dimensions can be different from one cluster to another. A new challenging research field has emerged, namely the subspace clustering. It is an extension of traditio¬ nal clustering that seeks to find clusters in different subspaces within a dataset. Image processing and image analysis tools are widely used in different domains. However, exploi¬ ting these images is tightly dependant of their textures. In this work, we have developed
two approaches to image classification. The first one is a subspace clustering method. It is an iterative algorithm based on the minimization of an objective function. This function is formed by a separation and compactness terms. The cluster density is also introduced in the compactness term. An initialization step has been improved by a multi class SVM algorithm. An active learning with SVM is incorporated in the classification process to speed the proposed algorithm convergence. It allows enhancing the cluster center loca¬ tion. The second approach is based on a new non linear model which extends the random coefficients autoregressive model (RCA) to a bidimensionally RCA model (2D-RCA).The coefficients are estimated by the generalized moments method (GMM). It is a supervised method.
We have proposed different versions of classification algorithms. The developed approaches have been tested and evaluated on different synthetic datasets and textures and real images. Experimental results have corroborated the effectiveness of the proposed method compared to well-established and state-of-the-art methods.
Diplôme : Magistère En ligne : ../theses/electronique/BOU6972.pdf Format de la ressource électronique : Permalink : https://bu.umc.edu.dz/md/index.php?lvl=notice_display&id=10370 Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité BOU/6972 BOU/6972 Thèse Bibliothèque principale Thèses Disponible
Titre : Débruitage d’images médicales par modélisation stochastique spatiale. Type de document : texte imprimé Auteurs : Safia Raslain, Auteur ; Fella Hachouf, Directeur de thèse Editeur : جامعة الإخوة منتوري قسنطينة Année de publication : 2019 Importance : 104 f. Format : 30 cm. Note générale : Doctorat 3éme CYCLE LMD.
2 copies imprimées disponiblesLangues : Français (fre) Catégories : Français - Anglais
ElectroniqueTags : Electronique: Automatique et Traitement du signal images ultrasonors (US) dé-bruitage d’image méthode des moments généralisés (GMM) modélisation 2D GARCH Erreur quadratique
moyenne minimale(MMSE) Ultrasound (US) medical images image denoising generalized method of moments (GMM) 2D GARCH modeling Minimum Mean Square Error (MMSE) صور الموجات فوق الصوتية إزالة الضوضاء طريقة اللحضات المعممة اللحظات
GMM طريقة الحد الأدنى للخطا المتوسط MMSE نمودج 2D GARCHIndex. décimale : 621 Electronique Résumé :
Ultrasound medical images de-noising is an important field that is used infinitely in image processing, where images are corrupted by multiplicative noise called speckle. Different methods and techniques should be used to remove these noises. This thesis presents a novel approach for ultrasound (US)images denoising. This is a class of Generalized Moment Method (GMM) estimators with interesting asymptotic properties for 2D GARCH modeling of wavelet coefficients. Indeed, these estimators are used to suppress noise in US images. An MMSE (Minimum Mean Square Error)
method is applied to estimate the wavelet coefficients of the clear image. To judge the quality of the noise reduction procedure, a link between the noise reduction efficiency procedure and a proposed asymmetry measurement is established. Several tests were conducted to prove the performance of the proposed approach. The results obtained are compared to those of well-established image de-noising methods using the usual image quality assessment metrics and two proposed no-reference quality metrics.
Note de contenu :
Annexe.
Diplôme : Doctorat En ligne : ../theses/electronique/RAS7499.pdf Format de la ressource électronique : Permalink : https://bu.umc.edu.dz/md/index.php?lvl=notice_display&id=11331 Débruitage d’images médicales par modélisation stochastique spatiale. [texte imprimé] / Safia Raslain, Auteur ; Fella Hachouf, Directeur de thèse . - جامعة الإخوة منتوري قسنطينة, 2019 . - 104 f. ; 30 cm.
Doctorat 3éme CYCLE LMD.
2 copies imprimées disponibles
Langues : Français (fre)
Catégories : Français - Anglais
ElectroniqueTags : Electronique: Automatique et Traitement du signal images ultrasonors (US) dé-bruitage d’image méthode des moments généralisés (GMM) modélisation 2D GARCH Erreur quadratique
moyenne minimale(MMSE) Ultrasound (US) medical images image denoising generalized method of moments (GMM) 2D GARCH modeling Minimum Mean Square Error (MMSE) صور الموجات فوق الصوتية إزالة الضوضاء طريقة اللحضات المعممة اللحظات
GMM طريقة الحد الأدنى للخطا المتوسط MMSE نمودج 2D GARCHIndex. décimale : 621 Electronique Résumé :
Ultrasound medical images de-noising is an important field that is used infinitely in image processing, where images are corrupted by multiplicative noise called speckle. Different methods and techniques should be used to remove these noises. This thesis presents a novel approach for ultrasound (US)images denoising. This is a class of Generalized Moment Method (GMM) estimators with interesting asymptotic properties for 2D GARCH modeling of wavelet coefficients. Indeed, these estimators are used to suppress noise in US images. An MMSE (Minimum Mean Square Error)
method is applied to estimate the wavelet coefficients of the clear image. To judge the quality of the noise reduction procedure, a link between the noise reduction efficiency procedure and a proposed asymmetry measurement is established. Several tests were conducted to prove the performance of the proposed approach. The results obtained are compared to those of well-established image de-noising methods using the usual image quality assessment metrics and two proposed no-reference quality metrics.
Note de contenu :
Annexe.
Diplôme : Doctorat En ligne : ../theses/electronique/RAS7499.pdf Format de la ressource électronique : Permalink : https://bu.umc.edu.dz/md/index.php?lvl=notice_display&id=11331 Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité RAS/7499 RAS/7499 Thèse Bibliothèque principale Thèses Disponible
Titre : Évaluation de la qualité perceptuelle des signaux multimédias : Évaluation multi-critère basée sur la fusion des métriques. Type de document : texte imprimé Auteurs : Borhen Eddine Dakkar, Auteur ; Fella Hachouf, Directeur de thèse Editeur : جامعة الإخوة منتوري قسنطينة Année de publication : 2017 Importance : 109 f. Format : 30 cm. Note générale : 2 copies imprimées disponibles. Langues : Français (fre) Catégories : Français - Anglais
ElectroniqueTags : Qualité d’image sans référence fusion de mesures évaluation de la qualité perceptuelle machine à vecteur de support optimisation des essaimes de particules vision binoculaire No reference image quality metric fusion perceptual quality evaluation support vector regression particle swarm optimization binocular vision القياس الكمي لنوعية الصورة دمج المقاييس الجودة الادراكية للصورة نظريات التراجع خوارزمية التحيين من تنقل سرب الطيور نظرية محكاة العين البشرية Index. décimale : 621 Electronique Résumé : Quantifying image quality without reference is still a challenging problem, especially when different distortions affect the observed image. One no-reference metric is not able to assess the different distortions presented in the images. In this work, we have focused on the assessment based on a fusion scheme of multiple distortion measures. These metrics are built in two stages. First, a set of relevant image quality assessment metrics is used to evaluate the perceptual quality. Then, a support vector regression (SVR)-based fusion strategy is adopted to derive the overall index of image quality.
For the 2D metric, we have used the particle swarm optimization to select the appropriate metrics. While for the 3D metric, we have incorporated the binocular vision in the assessment process. To evaluate the performance of the proposed metrics, different image databases have been used. The obtained results demonstrate clearly that the proposed approaches outperform the stateof-the-art NR-IQA methods. Furthermore, the proposed approaches are flexible and could be extended to other distortions.
Diplôme : Doctorat En ligne : ../theses/electronique/DAR7198.pdf Format de la ressource électronique : Permalink : https://bu.umc.edu.dz/md/index.php?lvl=notice_display&id=10765 Évaluation de la qualité perceptuelle des signaux multimédias : Évaluation multi-critère basée sur la fusion des métriques. [texte imprimé] / Borhen Eddine Dakkar, Auteur ; Fella Hachouf, Directeur de thèse . - جامعة الإخوة منتوري قسنطينة, 2017 . - 109 f. ; 30 cm.
2 copies imprimées disponibles.
Langues : Français (fre)
Catégories : Français - Anglais
ElectroniqueTags : Qualité d’image sans référence fusion de mesures évaluation de la qualité perceptuelle machine à vecteur de support optimisation des essaimes de particules vision binoculaire No reference image quality metric fusion perceptual quality evaluation support vector regression particle swarm optimization binocular vision القياس الكمي لنوعية الصورة دمج المقاييس الجودة الادراكية للصورة نظريات التراجع خوارزمية التحيين من تنقل سرب الطيور نظرية محكاة العين البشرية Index. décimale : 621 Electronique Résumé : Quantifying image quality without reference is still a challenging problem, especially when different distortions affect the observed image. One no-reference metric is not able to assess the different distortions presented in the images. In this work, we have focused on the assessment based on a fusion scheme of multiple distortion measures. These metrics are built in two stages. First, a set of relevant image quality assessment metrics is used to evaluate the perceptual quality. Then, a support vector regression (SVR)-based fusion strategy is adopted to derive the overall index of image quality.
For the 2D metric, we have used the particle swarm optimization to select the appropriate metrics. While for the 3D metric, we have incorporated the binocular vision in the assessment process. To evaluate the performance of the proposed metrics, different image databases have been used. The obtained results demonstrate clearly that the proposed approaches outperform the stateof-the-art NR-IQA methods. Furthermore, the proposed approaches are flexible and could be extended to other distortions.
Diplôme : Doctorat En ligne : ../theses/electronique/DAR7198.pdf Format de la ressource électronique : Permalink : https://bu.umc.edu.dz/md/index.php?lvl=notice_display&id=10765 Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité DAR/7198 DAR/7198 Thèse Bibliothèque principale Thèses Disponible
Titre : No-reference stereoscopic image quality assessment. Type de document : texte imprimé Auteurs : Oussama Messai, Auteur ; Fella Hachouf, Directeur de thèse ; Zianou Ahmed Seghir, Directeur de thèse Mention d'édition : 16/12/2021 Editeur : جامعة الإخوة منتوري قسنطينة Année de publication : 2021 Importance : 161 f. Format : 30 cm. Note générale : Doctorat 3éme CYCLE LMD.
1 copies imprimées disponibles
Langues : Anglais (eng) Catégories : Français - Anglais
ElectroniqueTags : Electronique: Automatique et Traitement du signal ( Automatic and signal processing) Evaluation de la qualité d’image stéréoscopique (SIQA) système visuel humain (HVS) informations de saillance apprentissage en profondeur Stereoscopic Image Quality Assessment (SIQA) Human Visual System (HVS) Saliency information Deep learning تقييم جودة الصورة المجسمة النظام البصري البشري معلومات التميز التعلم العميق Index. décimale : 621 Electronique Résumé :
Stereoscopic imaging is becoming increasingly popular, and its use in photography, television, and films is rapidly expanding. Obviously, access to this type of images often includes necessary treatments (acquisition, processing, compression, transmission, etc.), which may result in a variety of artifacts (blocking, blur, ringing, etc.). As a result, it is critical to have adequate tools for measuring the quality of stereoscopic contents. It is thus essential to establish efficient metrics that assess the impact of these treatments on the perceived quality. To meet this critical need, significant efforts have been made to study and evaluate the quality of stereoscopic images. In this thesis, we present several contributions for quality assessment of stereoscopic contents. Five methods have been proposed in total, with all of them are no-reference based metric. These metrics were developed with Human Visual System (HVS) modeling and human visual attention (saliency information) in mind. In addition, various advanced techniques, such as deep learning, have been incorporated into our workflow designs.
Diplôme : Doctorat En ligne : ../theses/electronique/MES7843.pdf Format de la ressource électronique : Permalink : https://bu.umc.edu.dz/md/index.php?lvl=notice_display&id=11717 No-reference stereoscopic image quality assessment. [texte imprimé] / Oussama Messai, Auteur ; Fella Hachouf, Directeur de thèse ; Zianou Ahmed Seghir, Directeur de thèse . - 16/12/2021 . - جامعة الإخوة منتوري قسنطينة, 2021 . - 161 f. ; 30 cm.
Doctorat 3éme CYCLE LMD.
1 copies imprimées disponibles
Langues : Anglais (eng)
Catégories : Français - Anglais
ElectroniqueTags : Electronique: Automatique et Traitement du signal ( Automatic and signal processing) Evaluation de la qualité d’image stéréoscopique (SIQA) système visuel humain (HVS) informations de saillance apprentissage en profondeur Stereoscopic Image Quality Assessment (SIQA) Human Visual System (HVS) Saliency information Deep learning تقييم جودة الصورة المجسمة النظام البصري البشري معلومات التميز التعلم العميق Index. décimale : 621 Electronique Résumé :
Stereoscopic imaging is becoming increasingly popular, and its use in photography, television, and films is rapidly expanding. Obviously, access to this type of images often includes necessary treatments (acquisition, processing, compression, transmission, etc.), which may result in a variety of artifacts (blocking, blur, ringing, etc.). As a result, it is critical to have adequate tools for measuring the quality of stereoscopic contents. It is thus essential to establish efficient metrics that assess the impact of these treatments on the perceived quality. To meet this critical need, significant efforts have been made to study and evaluate the quality of stereoscopic images. In this thesis, we present several contributions for quality assessment of stereoscopic contents. Five methods have been proposed in total, with all of them are no-reference based metric. These metrics were developed with Human Visual System (HVS) modeling and human visual attention (saliency information) in mind. In addition, various advanced techniques, such as deep learning, have been incorporated into our workflow designs.
Diplôme : Doctorat En ligne : ../theses/electronique/MES7843.pdf Format de la ressource électronique : Permalink : https://bu.umc.edu.dz/md/index.php?lvl=notice_display&id=11717 Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité MES/7843 MES/7843 Thèse Bibliothèque principale Thèses Disponible Partitionnement neuronal et validité des classes. Application à la ségmentation d'images / Amel Boulemnadjel
PermalinkPermalink
