Browsing by Subject "Ottoman documents"

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Open Access
Did the Ottomans see UFOs? An 1838 Ottoman document about unusual celestial phenomenon
(Institut d’Études balkaniques & Centre de Thracologie, 2019) Radushev, Evgeni; Sabev, O.
The paper deals with an Ottoman document preserved in the Oriental Department of Sts. Cyril and Methodius National Library in Sofia. The document reveals that in October 1838 a heavy storm broke over in the night, followed by appearance of a round-shaped bright light. It illuminated the whole horizon and afterwards broke into pieces that fell down on the earth. The unusual celestial phenomenon was observed by the Ottoman soldiers camping nearby Mardin as well as the locals. They reported the case to the sultan, who was informed also of the opinion of the local men of religion, whose interpretation associated the phenomenon with a divine sign of forthcoming military victories.
Open Access
Matching ottoman words: an image retrieval approach to historical document indexing
(ACM, 2007-07) Ataer, Esra; Duygulu, Pınar
Large archives of Ottoman documents are challenging to many historians all over the world. However, these archives remain inaccessible since manual transcription of such a huge volume is difficult. Automatic transcription is required, but due to the characteristics of Ottoman documents, character recognition based systems may not yield satisfactory results. It is also desirable to store the documents in image form since the documents may contain important drawings, especially the signatures. Due to these reasons, in this study we treat the problem as an image retrieval problem with the view that Ottoman words are images, and we propose a solution based on image matching techniques. The bag-of-visterms approach, which is shown to be successful to classify objects and scenes, is adapted for matching word images. Each word image is represented by a set of visual terms which are obtained by vector quantization of SIFT descriptors extracted from salient points. Similar words are then matched based on the similarity of the distributions of the visual terms. The experiments are carried out on printed and handwritten documents which included over 10,000 words. The results show that, the proposed system is able to retrieve words with high accuracies, and capture the semantic similarities between words. Copyright 2007 ACM.