Setitra, InsafMeziane, Abdelkrim2014-10-232014-10-232014-12http://dl.cerist.dz/handle/CERIST/691Manual 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.manuscript annotation;handwrittingcalligraphy classificationsupervised learningSVMPerimeter histogramConference paperIEEE