International Conference Papers
Permanent URI for this collectionhttp://dl.cerist.dz/handle/CERIST/4
Browse
6 results
Search Results
Item Classification automatique des images histologiques du cancer du sein par réseaux de neurones convolutifs (RNC)(Publication en ligne, 2018-08-01) Setitra, Insaf; Meziane, Abdelkrim; Mayouf, Mouna Sabrine; Hamrioui, AmelAprès le cancer de la peau, le cancer du sein est le deuxième type de cancer le plus commun chez la femme à l’échelle mondiale. Ce dernier enregistre un taux de mortalité assez élevé comparé aux autres types de cancer. (Spanhol, Oliveira et al. 2016). Le diagnostic des tumeurs du sein pour différencier les cellules bénignes des malignes établi par le pathologiste est le fruit d’un processus minutieux, fastidieux, long et sujet à plusieurs erreurs et divergence d’avis. Afin d’essayer de palier à ces inconvénients, un vif intérêt s’est porté sur l’automatisation du processus du diagnostic. Dans ce travail, nous reportons les différentes méthodes utilisées jusque-là par la communauté scientifique et nous exposons notre méthode basée sur la classification par réseaux de neurones convolutifs (RNC) qui sont un récent type de réseaux de neurones qui relie le traitement d’images à l’apprentissage automatique, afin de déterminer de la manière la plus précise le type tumoral.Item A Tracking Approach for Text Line Segmentation in Handwritten Documents(Springer / LNCS Series Book, 2017-02-24) Setitra, InsafTracking of objects in videos consists of giving a label to the same object moving in different frames. This labelling is performed by predicting position of the object given its set of features observed in previous frames. In this work, we apply the same rationale by considering each connected component in the manuscript as a moving object and to track it so that to minimize the distance and angle of of the connected component to its nearest neighbour. The approach was applied to images of ICDAR 2013 handwritten segmentation contest and proved to be robust against text orientation, size and writing script.Item A tracking approach for text line segmentation in handwritten documents(Springer, 2017-02-24) Setitra, Insaf; Hadjadj, Zineb; Meziane, AbdelkrimTracking of objects in videos consists of giving a label to the same object moving in different frames. This labeling is performed by predicting position of the object given its set of features observed in previous frames. In this work, we apply the same rationale by considering each connected component in the manuscript as a moving object and to track it so that to minimize the distance and angle of the connected component to its nearest neighbor. The approach was applied to images of ICDAR 2013 handwritten segmentation contest and proved to be robust against text orientation, size and writing script.Item Perimeter Histogram based Approach for Calligraphy Classification in Ancient Manuscripts(IEEE Xplore, 2014-12) Setitra, Insaf; Meziane, AbdelkrimManual annotation of images is usually a mandatory task in many applications where no knowledge about the image is available. In presence of huge number of images, this task becomes very tedious and prone to human errors. In this paper, we contribute in automatic annotation of ancient manuscripts by discovering manuscript calligraphy. Ancient manuscripts count a very large number of Persian and Maghrebi writing especially in Noth Africa. Distinguishing between these two calligraphies allows better classifying them and so annotating them. We use background constructing followed by extraction of simple features to classify manuscript calligraphies using an SVM classifier.Item A framework for Object Classification in Fareld Videos(Springer, 2014-12) Setitra, Insaf; Larabi, SlimaneObject classification in videos is an important step in many applications such as abnormal event detection in video surveillance, traf- fic analysis is urban scenes and behavior control in crowded locations. In this work, propose a framework for moving object classification in farfield videos. Much works have been dedicated to accomplish this task. We overview existing works and combine several techniques to implement a real time object classifier with offline training phase. We follow three main steps to classify objects in steady background videos : background subtraction, object tracking and classification. We measure accuracy of our classifier by experiments done using the PETS 2009 dataset.Item A simple approach to distinguish between Maghrebi and Persian calligraphy in old manuscripts(IAPR, 2014-04-07) Setitra, Insaf; Meziane, AbdelkrimManual annotation of images is usually a mandatory task in many applications where no knowledge about the image is available. In presence of huge number of images, this task becomes very tedious and prone to human errors. In this paper, we contribute in automatic annotation of Arabic old manuscripts by discovering manuscript calligraphy. Arabic manuscripts count a very large number of Persian and Maghrebi writing especially in Noth Africa. Distinguishing between these two calligraphies allow better classifying them and so annotating them. We use background constructing followed by extraction of simple features to classify Arabic manuscript calligraphies using a Quadratic Bayes classifier.