Abstract
In this paper, we propose a novel holistic methodology for keyword search in historical typewritten documents combining synthetic data and user’s feedback. The holistic approach treats the word as a single entity and entails the recognition of the whole word rather than of individual characters. Our aim is to search for keywords typed by the user in a large collection of digitized typewritten historical documents. The proposed method is based on: (i) creation of synthetic image words; (ii) word segmentation using dynamic parameters; (iii) efficient hybrid feature extraction for each image word and (iv) a retrieval procedure that is optimized by user’s feedback. Experimental results prove the efficiency of the proposed approach.
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Gatos, B., Konidaris, T., Pratikakis, I., Perantonis, S.J. (2006). A Holistic Methodology for Keyword Search in Historical Typewritten Documents. In: Antoniou, G., Potamias, G., Spyropoulos, C., Plexousakis, D. (eds) Advances in Artificial Intelligence. SETN 2006. Lecture Notes in Computer Science(), vol 3955. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11752912_52
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DOI: https://doi.org/10.1007/11752912_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34117-8
Online ISBN: 978-3-540-34118-5
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