Abstract
In this paper, we propose an approach to interactively propagate annotations representing the historians’ knowledge on a database of lettrine images manually populated by historians (with annotations). Based on a novel document indexing processing scheme which combines the use of the Zipf law and the use of bag of patterns, our approach extends the bag-of-words model to represent the knowledge by visual features through relevance feedback. Then, annotation propagation is automatically performed to propagate knowledge to the lettrine database. Our approach is presented together with preliminary experimental results and an illustrative example.










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Notes
The VHL is a team of the French historical center (CESR laboratory) working on documents from the Renaissance.
References
Bibliothèque nationale suisse. http://www.nb.admin.ch/slb/index.html. http://www.nb.admin.ch/slb/index.html?lang=fr
Bannour, H., Hudelot, C.: Towards ontologies for image interpretation and annotation. In: Content-Based Multimedia Indexing (CBMI), 2011 9th International Workshop on, pp. 211 –216 (2011)
Baudrier, E., Girard, N., Ogier, J.M.: A Non-symmetrical method of image local-difference comparison for ancient impressions dating. In: Seventh IAPR International Workshop on Graphics Recognition (GREC’07). Curitiba Brésil (2007)
Bigun, J., Bhattacharjee, S.K., Michel, S.: Orientation radiograms for image retrieval: an alternative to segmentation. In: Proceedings of 13th International Conference on Pattern Recognition, Vienna, Austria, vol. 3, pp. 346–350 (1996)
Bloehdorn, S., Petridis, K., Saathoff, C., Simou, N., Tzouvaras, V., Avrithis, Y., Handschuh, S., Kompatsiaris, Y., Staab, S., Strintzis, M.G.: Semantic annotation of images and videos for multimedia analysis. In: Proceedings of the Second European Conference on The Semantic Web: Research and Applications, ESWC’05, pp. 592–607. Springer, Berlin (2005)
Chazalon, J., Coüasnon, B.: Iterative analysis of document collections enables efficient human-initiated interaction. In: DRR (2012)
Chouaib, H., Cloppet, F., Vincent, N.: Graphical drop caps indexing. In: Ogier, J.M., Liu, W., Lladós, J. (eds.) Graphics Recognition. Achievements, Challenges, and Evolution. LNCS, vol. 6020, pp. 212–219. Springer, Berlin (2010)
Corrêa, G.N., Marcacini, R.M., Hruschka, E.R., Rezende, S.O.: Interactive textual feature selection for consensus clustering. Pattern Recogn. Lett. 52(C), 25–31 (2015). https://doi.org/10.1016/j.patrec.2014.09.008
Coustaty, M., Ogier, J.M.: Discrimination of old document images using their style. In: International Conference on Document Analysis and Recognition, pp. 389–393 (2011)
Coustaty, M., Pareti, R., Vincent, N., Ogier, J.M.: Towards historical document indexing: extraction of drop cap letters. Int. J. Doc. Anal. Recognit. 14(3), 1–12 (2011)
Filali, J., Zghal, H.B., Martinet, J.: Towards visual vocabulary and ontology-based image retrieval system. In: International Conference on Agents and Artificial Intelligence , International Conference on Agents and Artificial Intelligence, vol. 2, pp. 560 – 565. Rome, Italy (2016). https://doi.org/10.5220/0005832805600565. https://hal.archives-ouvertes.fr/hal-01557742
Frigui, H., Krishnapuram, R.: Clustering by competitive agglomeration. Pattern Recognit. 30(7), 1109–1119 (1997)
Gao, H., Rusiñol, M., Karatzas, D., Antonacopoulos, A., Lladós, J.: An interactive appearance-based document retrieval system for historical newspapers. VISAPP 2, 84–87 (2013)
Ghorbel, A., Almaksour, A., Lemaitre, A., Anquetil, É.: Incremental learning for interactive sketch recognition. In: GREC, pp. 108–118 (2011)
Hechenbichler, W., Schliep, K.: Weighted k-nearest-neighbor techniques and ordinal classification. In: SFB Discussion paper 399 (2004)
Jain, A.K., Dubes, R.C.: Algorithms for Clustering Data. Prentice-Hall Inc., Upper Saddle River (1988)
Jiang, W., Chan, K.L., Li, M., Zhang, H.: Mapping low-level features to high-level semantic concepts in region-based image retrieval. In: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05), vol. 2, pp. 244–249 (2005). https://doi.org/10.1109/CVPR.2005.220
Jones, K.S.: Experiments in relevance weighting of search terms. Inf. Process. Manag. 15(3), 133–144 (1979)
Journet, N., Ramel, J.Y., Mullot, R., Eglin, V.: Document image characterization using a multiresolution analysis of the texture: application to old documents. IJDAR 11(1), 9–18 (2008)
Karatzas, D., d’Andecy, V.P., Rusiñol, M., Chica, A., Vázquez, P.P.: Human-document interaction systems: a new frontier for document image analysis. In: Proceedings of the International Workshop on Document Analysis Systems (DAS) (2016)
Kothari, R., Pitts, D.: On finding the number of clusters. Pattern Recognit. Lett. 20(4), 405–416 (1999)
Lin, W.C., Chang, Y.C., Chen, H.H.: Integrating textual and visual information for cross-language image retrieval: a trans-media dictionary approach. Inf. Process. Manag. 43(2), 488–502 (2007)
Lladós, J., Rusiñol, M., Fornés, A., Fernández, D., Dutta, A.: On the influence of word representations for handwritten word spotting in historical documents. Int. J. Pattern Recognit. Artif. Intell. 26(05), 1263002 (2012). https://doi.org/10.1142/S0218001412630025
Nguyen, N., Boucher, A., Ogier, J.: Keyword visual representation for image retrieval and image annotation. IJPRAI 29(6), 1555010 (2015). https://doi.org/10.1142/S0218001415550101
Nguyen, N.V., Boucher, A., Ogier, J.M., Tabbone, S.: Cluster-based relevance feedback for CBIR: a combination of query point movement and query expansion. J. Ambient Intell. Humaniz. Comput. 3(4), 281–292 (2012)
Nourashrafeddin, S., Sherkat, E., Minghim, R., Milios, E.E.: A visual approach for interactive keyterm-based clustering. ACM Trans. Interact. Intell. Syst. 8(1), 6:1–6:35 (2018). https://doi.org/10.1145/3181669
Pal, K., Schüller, C., Panozzo, D., Sorkine-Hornung, O., Weyrich, T.: Content-aware surface parameterization for interactive restoration of historical documents. Comput. Graph. Forum 33(2), 401–409 (2014). https://doi.org/10.1111/cgf.12299
Pareti, R., Vincent, N.: Global discrimination of graphic styles. In: GREC, pp. 120–130 (2005)
Pareti, R., Vincent, N.: Ancient initial letters indexing. In: 18th International Conference on Pattern Recognition, pp. 756–759. IEEE Computer Society, Hong Kong, China (2006)
Purday, J.: Think culture: Europeana.eu from concept to construction. Electron. Libr. 27(6), 919–937 (2009)
Rocchio, J.: Relevance Feedback in Information Retrieval, pp. 313–323. Prentice Hall, Englewood Cliffs (1971)
Rusiñol, M., Lladós, J.: Boosting the handwritten word spotting experience by including the user in the loop. Pattern Recognit. 47(3), 1063–1072 (2014). https://doi.org/10.1016/j.patcog.2013.07.008
Rusiñol, M., Lladós, J.: The role of the users in handwritten word spotting applications: query fusion and relevance feedback. In: ICFHR, pp. 55–60 (2012)
Sherkat, E., Nourashrafeddin, S., Minghim, R., Milios, E.: A visual approach for interactive expertise finding and exploration. In: CIKM 2016 Workshop on Data-Driven Talent Acquisition (2016)
Sivic, J., Zisserman, A.: Efficient visual search for objects in videos. Proc. IEEE 96, 548–566 (2008)
Valveny, E., Ramos, O., Mas, J., Rossinyol, M.: Interactive document retrieval and classification. In: Multimodal Interaction in Image and Video Applications. Springer, Berlin (2016)
Vats, E., Hast, A.: On-the-fly historical handwritten text annotation. In: 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR), Kyoto, pp. 10–14 (2017)
Ward, J.: Hierarchical grouping to optimize an objective function. J. Am. Stat. Assoc. 58, 236–244 (1963)
Xie, H., Zhang, Y., Tan, J., Guo, L., Li, J.: Contextual query expansion for image retrieval. IEEE Trans. Multimedia 16(4), 1104–1114 (2014)
Xie, R., Liu, Z., Luan, H., Sun, M.: Image-embodied knowledge representation learning. In: IJCAI (2017)
Zaghden, N., Mullot, R., Alimi, M.A.: A proposition of a robust system for historical document images indexation. arXiv preprint arXiv:1308.6319 (2013)
Zhao, R., Grosky, W.I.: Narrowing the semantic gap-improved text-based web document retrieval using visual features. IEEE Trans. Multimedia 4(2), 189–200 (2002)
Zipf, G.: Human Behavior and the Principle of Least Effort. Hafner Pub. Co, New York (1949)
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Nguyen, NV., Coustaty, M. & Ogier, JM. An adaptive document recognition system for lettrines. IJDAR 23, 115–128 (2020). https://doi.org/10.1007/s10032-019-00346-9
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DOI: https://doi.org/10.1007/s10032-019-00346-9