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A word spotting framework for historical machine-printed documents

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Abstract

In this paper, we propose a word spotting framework for accessing the content of historical machine-printed documents without the use of an optical character recognition engine. A preprocessing step is performed in order to improve the quality of the document images, while word segmentation is accomplished with the use of two complementary segmentation methodologies. In the proposed methodology, synthetic word images are created from keywords, and these images are compared to all the words in the digitized documents. A user feedback process is used in order to refine the search procedure. The methodology has been evaluated in early Modern Greek documents printed during the seventeenth and eighteenth century. In order to improve the efficiency of accessing and search, natural language processing techniques have been addressed that comprise a morphological generator that enables searching in documents using only a base word-form for locating all the corresponding inflected word-forms and a synonym dictionary that further facilitates access to the semantic context of documents.

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Authors and Affiliations

  1. Computational Intelligence Laboratory, Institute of Informatics and Telecommunications, National Center for Scientific Research “Demokritos”, 15310, Agia Paraskevi, Athens, Greece

    A. L. Kesidis, B. Gatos & I. Pratikakis

  2. Department of Surveying Engineering, Technological Educational Institution of Athens, Ag. Spyridona, 12210, Egaleo, Athens, Greece

    A. L. Kesidis

  3. Department of Informatics, Technological Educational Institution of Athens, Ag. Spyridona, 12210, Egaleo, Athens, Greece

    E. Galiotou

  4. Department of Electrical and Computer Engineering, Democritus University of Thrace, 67100, Xanthi, Greece

    I. Pratikakis

Authors
  1. A. L. Kesidis
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  2. E. Galiotou
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  3. B. Gatos
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  4. I. Pratikakis
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Correspondence to A. L. Kesidis.

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Kesidis, A.L., Galiotou, E., Gatos, B. et al. A word spotting framework for historical machine-printed documents. IJDAR 14, 131–144 (2011). https://doi.org/10.1007/s10032-010-0134-4

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  • DOI: https://doi.org/10.1007/s10032-010-0134-4

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