Perimeter Histogram based Approach for Calligraphy Classification in Ancient Manuscripts

dc.citation.volume4fr_FR
dc.contributor.authorSetitra, Insaf
dc.contributor.authorMeziane, Abdelkrim
dc.date.accessioned2014-10-23T12:27:01Z
dc.date.available2014-10-23T12:27:01Z
dc.date.issued2014-12
dc.description.abstractManual 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.fr_FR
dc.identifier.urihttp://dl.cerist.dz/handle/CERIST/691
dc.publisherIEEE Xplorefr_FR
dc.relation.ispartofISKO maghreb 2014fr_FR
dc.relation.placeAlger, Algériefr_FR
dc.rights.holderIEEEfr_FR
dc.structureSystèmes d'Information et Image en Santé (S2IS)fr_FR
dc.structureTechnologies des Systèmes Web et Multimédia et de Gestion de Contenufr_FR
dc.structureSystèmes et Documents Multimédia Structurés (SDMS)fr_FR
dc.subjectmanuscript annotation;fr_FR
dc.subjecthandwrittingfr_FR
dc.subjectcalligraphy classificationfr_FR
dc.subjectsupervised learningfr_FR
dc.subjectSVMfr_FR
dc.subjectPerimeter histogramfr_FR
dc.titlePerimeter Histogram based Approach for Calligraphy Classification in Ancient Manuscriptsfr_FR
dc.typeConference paper
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