caa a22 4500 445379669 CHVBK 20180317143013.0 cr unu---uuuuu 170323e20110601xx s 000 0 eng 10.1007/s10032-010-0134-4 doi (NATIONALLICENCE)springer-10.1007/s10032-010-0134-4 A word spotting framework for historical machine-printed documents [Elektronische Daten] [A. Kesidis, E. Galiotou, B. Gatos, I. Pratikakis] 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. Springer-Verlag, 2010 Historical document indexing nationallicence Word spotting nationallicence Natural language processing nationallicence Computational morphology nationallicence Kesidis A. Computational Intelligence Laboratory, Institute of Informatics and Telecommunications, National Center for Scientific Research "Demokritos”, 15310, Agia Paraskevi, Athens, Greece aut Galiotou E. Department of Informatics, Technological Educational Institution of Athens, Ag. Spyridona, 12210, Egaleo, Athens, Greece aut Gatos B. Computational Intelligence Laboratory, Institute of Informatics and Telecommunications, National Center for Scientific Research "Demokritos”, 15310, Agia Paraskevi, Athens, Greece aut Pratikakis I. Computational Intelligence Laboratory, Institute of Informatics and Telecommunications, National Center for Scientific Research "Demokritos”, 15310, Agia Paraskevi, Athens, Greece aut International Journal on Document Analysis and Recognition (IJDAR) Springer-Verlag 14/2(2011-06-01), 131-144 1433-2833 14:2<131 2011 14 10032 https://doi.org/10.1007/s10032-010-0134-4 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10032-010-0134-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Kesidis A. Computational Intelligence Laboratory, Institute of Informatics and Telecommunications, National Center for Scientific Research "Demokritos”, 15310, Agia Paraskevi, Athens, Greece aut NATIONALLICENCE 700 1- Galiotou E. Department of Informatics, Technological Educational Institution of Athens, Ag. Spyridona, 12210, Egaleo, Athens, Greece aut NATIONALLICENCE 700 1- Gatos B. Computational Intelligence Laboratory, Institute of Informatics and Telecommunications, National Center for Scientific Research "Demokritos”, 15310, Agia Paraskevi, Athens, Greece aut NATIONALLICENCE 700 1- Pratikakis I. Computational Intelligence Laboratory, Institute of Informatics and Telecommunications, National Center for Scientific Research "Demokritos”, 15310, Agia Paraskevi, Athens, Greece aut NATIONALLICENCE 773 0- International Journal on Document Analysis and Recognition (IJDAR) Springer-Verlag 14/2(2011-06-01), 131-144 1433-2833 14:2<131 2011 14 10032 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer