Browsing by Subject "Photocopying"

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Open Access
A layout algorithm for undirected compound graphs
(Elsevier, 2009-03-15) Doğrusöz, Uğur; Giral, Erhan; Çetintaş, Ahmet; Civril, Ali; Demir, Emek
We present an algorithm for the layout of undirected compound graphs, relaxing restrictions of previously known algorithms in regards to topology and geometry. The algorithm is based on the traditional force-directed layout scheme with extensions to handle multi-level nesting, edges between nodes of arbitrary nesting levels, varying node sizes, and other possible application-specific constraints. Experimental results show that the execution time and quality of the produced drawings with respect to commonly accepted layout criteria are quite satisfactory. The algorithm has also been successfully implemented as part of a pathway integration and analysis toolkit named PATIKA, for drawing complicated biological pathways with compartmental constraints and arbitrary nesting relations to represent molecular complexes and various types of pathway abstractions. © 2008 Elsevier Inc. All rights reserved.
Open Access
Osmanlıca kelimeleri eşleme
(IEEE, 2007-06) Ataer, Esra; Duygulu, Pınar
Osmanlı arşivleri dünyanın pek çok yerinden araştırmacının ilgi alanına girmektedir. Fakat bu belgelerin elle çevirisi zor bir iş olduğu için, bu arşivler kullanılamaz durumdadır. Otomatik çeviri gerekmektedir, fakat Osmanlıca’nın yazma özelliklerinden dolayı karakter tabanlı tanıma sistemleri istenen başarıyı gösterememektedir. Ayrıca, belgeler minyatür ve tuğra gibi önemli kısımlar içerdiği için, imge formatında saklanmaları gerekmektedir. Bu nedenle, bu çalışmada Osmanlıca kelimeleri imge olarak görerek probleme imge erişim problemi olarak yaklaşıldı ve kelime eşleme tekniği üzerine bir çözüm önerisinde bulunuldu. Nesne tanımada başarılı olan görsel öğeler kümesi (bag-of-visterms) tekniği kelime eşleme işlemine uyarlandı ve böylece her kelime imgesi taç noktalarından çıkarılan SIFT özelliklerinin ¨ vektor¨ nicemlemesiyle sembolize edildi. Benzer kelimeler görsel ögelerin dağılımına göre eşlendi. Deneyler 10,000 kelimenin üzerindeki matbu ve elyazması belge üzerinde yapıldı. Sonuçlar sistemin benzer kelimeleri yüksek doğrulukla eşlediğini ve anlamsal benzerlikleri bulduğunu gösteriyor 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.