Matching ottoman words: an image retrieval approach to historical document indexing
Author
Ataer, Esra
Duygulu, Pınar
Date
2007-07Source Title
Proceedings of the 6th ACM International Conference on Image and Video Retrieval, CIVR 2007
Publisher
ACM
Pages
341 - 347
Language
English
Type
Conference PaperItem Usage Stats
109
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115
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Abstract
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.
Keywords
Bag-of-featuresIndexing
Word-image matching
Character recognition equipment
Historic preservation
Image matching
Indexing (of information)
Semantics
Vector quantization
Automatic transcription
Historical document indexing
Manual transcription
Ottoman documents
Recognition based systems
Image retrieval