Abstract
In this paper, we address the problem of document image retrieval in digital libraries. As an essential element of this problem we have proposed a measure of spatial layout similarity with importance to category of components in document images. We have tested the method on MediaTeam document image database that provides diverse collection of document images.
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References
Appiani, E., et al.: Automatic document classification and indexing in high-volume applications. Int’l Journal on Document Analysis and Recognition 4, 69–83 (2001)
Chalechale, A., Naghdy, G., Mertins, A.: Signature-based Document Retrieval. In: Proc. of 3rd IEEE Int’l Symposium on Signal Processing and Information Technology, pp. 597–600. IEEE Computer Society Press, Los Alamitos (2003)
Cullen, J.F., Hull, J.J., Hart, P.E.: Document Image Database Retrieval and Browsing using Texture Analysis. In: Proc. Fourth Int’l Conf. Document Analysis and Recognition, pp. 718–721 (1997)
Das, A.K., Chanda, B.: A fast algorithm for skew detection of document images using morphology. Int’l Journal on Document Analysis and Recognition 4, 109–114 (2001)
Das, A.K., Saha, S.K., Chanda, B.: An empirical measure of the performance of a document image segmentation algorithm. Int’l Journal on Document Analysis and Recognition 4, 183–190 (2002)
Doermann, D.: The Retrieval of Document Images: A Brief Survey. In: Proc. Fourth Int’l Conf. Document Analysis and Recognition, pp. 945–949 (1997)
Doermann, D., et al.: The development of a general framework for intelligent document image retrieval. In: Proc. of Document Analysis sytems workshop, pp. 605–632 (1996)
Eglin, V., Bres, S.: Document page similarity based on layout based on layout visual saliency: Application to query by example and document classification. In: Proc. Seventh Int’l Conf. Document Analysis and Recognition, pp. 1208–1212 (2003)
Guru, D.S., Punitha, P., Mahesh, S.: Skew Estimation in Digitized Documents: A Novel Approach. In: Proc. Forth Indian Conf. on Computer Vision, Graphics & Image Processing, pp. 314–319 (2004)
Hu, J., Kashi, R., Wilfong, G.: Document Image Layout Comparison and Classification. In: Proc. Fifth Int’l Conf. on Document Analysis and Recognition, pp. 285–289 (1999)
Jain, A.K., Liu, J.: Image-Based Form Document Retrieval. In: 14th International Conference on Pattern Recognition, vol. 1, pp. 626–629 (1998)
Jain, A.K., Yu, B.: Document Representation and Its Application to Page Decomposition. IEEE Trans. on Pattern Analysis and Machine Intelligence 20(3), 294–308 (1998)
Jaisimha, M.Y., Bruce, A., Nguyen, T.: Docbrowse: A system for textual and graphical querying on degraded document image data. In: DAS, pp. 581–604 (1996)
Lee, S.-W., Ryu, D.-S.: Parameter-Free Geometric Document Layout Analysis. IEEE Trans. on Pattern Analysis and Machine Intelligence 23(11), 1240–1256 (2001)
Marinai, S., et al.: A General System for the Retrieval of Document Images from Digital Libraries. In: First Int’l Workshop on Document Image Analysis for Libraries(DIAL’04), pp. 150–173 (2004)
Sauvola, J., Kauniskangas, H.: MediaTeam Document Database II, a CD-ROM collection of document images, University of Oulu, Finland (1999)
Shin, C., Doermann, D., Rosenfeld, A.: Classification of document pages using structure-based features. Int’l Journal on Document Analysis and Recognition 3, 232–247 (2001)
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Naveen, Guru, D.S. (2007). Retrieval of Document Images Based on Page Layout Similarity. In: Marchand-Maillet, S., Bruno, E., Nürnberger, A., Detyniecki, M. (eds) Adaptive Multimedia Retrieval: User, Context, and Feedback. AMR 2006. Lecture Notes in Computer Science, vol 4398. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71545-0_11
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DOI: https://doi.org/10.1007/978-3-540-71545-0_11
Publisher Name: Springer, Berlin, Heidelberg
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