E.: Content-based retrieval of historical Ottoman documents stored as textual images

Abstract—There is an accelerating demand to access the visual content of documents stored in historical and cultural archives. Availability of electronic imaging tools and effective image processing techniques makes it feasible to process the multimedia data in large databases. In this paper, a fram...

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Bibliographic Details
Main Authors: Ali Kemal Sinop, Özgür Ulusoy, A. Enis Çetin, Senior Member
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Published: 2004
Subjects:
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.63.7713
http://www.cs.bilkent.edu.tr/~oulusoy/ieee_tip.pdf
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Summary:Abstract—There is an accelerating demand to access the visual content of documents stored in historical and cultural archives. Availability of electronic imaging tools and effective image processing techniques makes it feasible to process the multimedia data in large databases. In this paper, a framework for content-based retrieval of historical documents in the Ottoman Empire archives is presented. The documents are stored as textual images, which are compressed by constructing a library of symbols occurring in a document, and the symbols in the original image are then replaced with pointers into the codebook to obtain a compressed representation of the image. The features in wavelet and spatial domain based on angular and distance span of shapes are used to extract the symbols. In order to make content-based retrieval in historical archives, a query is specified as a rectangular region in an input image and the same symbol-extraction process is applied to the query region. The queries are processed on the codebook of documents and the query images are identified in the resulting documents using the pointers in textual images. The querying process does not require decompression of images. The new content-based retrieval framework is also applicable to many other document archives using different scripts. Index Terms—Angular and distance span, binary wavelet decomposition, content-based retrieval, historical document compression, partial symbol-wise matching. I.