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 Our aim is to search for keywords typed by the user in a large collection of digitized typewritten historical documents.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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References
Baird, H.S.: The state of the art of document image degradation modeling. In: IARP 2000 Workshop on Document Analysis Systems, pp. 10–13 (2000)
Bhat, D.: An evolutionary measure for image matching. In: Proceedings of the Fourteenth International Conference on Pattern Recognition, ICPR 1998, vol. I, pp. 850–852 (1998)
Bokser, M.: Omnidocument technologies. Proceedings of the IEEE 80(7), 1066–1078 (1992)
Gatos, B., Papamarkos, N., Chamzas, C.: A binary tree based OCR technique for machine printed characters. Engineering Applications of Artificial Intelligence 10(4), 403–412 (1997)
Lu, Y., Tan, C., Weihua, H., Fan, L.: An approach to word image matching based on weighted Hausdorff distance. In: Sixth International Conference on Document Analysis and Recognition (ICDAR 2001), pp. 10–13 (2001)
Madhvanath, S., Govindaraju, V.: Local reference lines for handwritten word recognition. Pattern Recognition 32, 2021–2028 (1999)
Manmatha, R.: A scale space approach for automatically segmenting words from historical handwritten documents. IEEE Transactions on Pattern Analysis and Machine Intelligence 27(8), 1212–1225 (2005)
Marcolino, A., Ramos, V., Ármalo, M., Pinto, J.C.: Line and Word matching in old documents. In: Proceedings of the Fifth IberoAmerican Sympsium on Pattern Recognition (SIARP 2000), pp. 123–125 (2000)
Rath, T.M., Manmatha, R.: Features for word spotting in historical documents. In: Proceedings of the Seventh International Conference on Document Analysis and Recognition (ICDAR 2003), pp. 218–222 (2003)
Waked, B., Suen, C.Y., Bergler, S.: Segmenting document images using diagonal white runs and vertical edges. In: Proceedings of the Sixth International Conference on Document Analysis and Recognition (ICDAR 2001), pp. 194–199 (2001)
Weihua, H., Tan, C.L., Sung, S.Y., Xu, Y.: Word shape recognition for image-based document retrieval. In: International Conference on Image Processing, ICIP 2001, pp. 8–11 (2001)
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© 2006 Springer-Verlag Berlin Heidelberg
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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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