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Interactive high-dimensional index for large Chinese calligraphic character databases

Published: 01 September 2007 Publication History

Abstract

The large numbers of Chinese calligraphic scripts in existence are valuable part of the Chinese cultural heritage. However, due to the shape complexity of these characters, it is hard to employ existing techniques to effectively retrieve and efficiently index them. In this article, using a novel shape-similarity- based retrieval method in which shapes of calligraphic characters are represented by their contour points extracted from the character images, we propose an interactive partial-distance-map(PDM)- based high-dimensional indexing scheme which is designed specifically to speed up the retrieval performance of the large Chinese calligraphic character databases effectively. Specifically, we use the approximate minimal bounding sphere of a query character and utilize users' relevance feedback to refine the query gradually. Comprehensive experiments are conducted to testify the efficiency and effectiveness of this method. In addition, a new k-NN search called Pseudo k-NN (Pk-NN) search is presented to better facilitate the PDM-based character retrieval.

References

[1]
Beckmann, N., Kriegel, H. P., Schneider, R. and Seeger, B. 1990. The R*-tree: An Efficient and Robust Access Method for Characters and Rectangles, In: Proceedings of ACM SIGMOD International Conference on Management of Data. Philadelphia, pp. 322--331.
[2]
Belongie, S., Malik, J., and Puzicha, J., 2002. Shape Matching and Object Recognition Using Shape Contexts, IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 24, No. 4, pp. 509--522.
[3]
Bentley J. L. 1975. Multidimensional binary search trees used for associative searching. Communications of the ACM, Vol. 18, No. 9. pp. 509--517.
[4]
Berchtold, S., Keim, D. A., and Kriegel, H. P. 1996. The X-tree: An index structure for high- dimensional data. In: Proceedings of the International Conference on Very Large Data Base. Bombay, pp. 28--37.
[5]
Berchtold, S., Bohm, C., Kriegel, H. P, Sander, J., et al. 2000. Independent quantization: An index compression technique for high-dimensional data spaces. In: Proceedings of the International Conference on Data Engineering. San Diego, pp. 577--588.
[6]
Berchtold, S., Böhm, C., Keim, D., Krebs, F., and Kriegel, H. P. 2001. On Optimizing Nearest Neighbor Queries in High-Dimensional Data Spaces. In: Proceedings of the International Conference on Database Theory, London, pp. 435--449.
[7]
Böhm, C., Berchtold, S., and Keim, D. 2001. Searching in High-dimensional Spaces: Index Structures for Improving the Performance of Multimedia Databases, ACM Computing Surveys. Vol. 33, No. 3, pp. 322--373.
[8]
Chen, J. Y., Bouman, C. A., and Dalton, J. 2000. Hierarchical browsing and search of large image databases. IEEE Transaction on Image Processing. Vol. 9, No. 3, pp. 442--445.
[9]
Hui H. L., and Rangarajan, A. 2003. A new point matching algorithm for non-rigid registration, Computer Vision and Image Understanding archive,Vol. 89, No. 2-3. pp. 114--141.
[10]
Ciaccia, P., Patella, M., and Zezula, P. 1997. M-tree: An efficient access method for similarity search in metric spaces. In: Proceedings of the 23rd International Conference on Very Large Data Base, Greece, pp. 426--435.
[11]
Cohen, S., and Guibas, L. 1999. The Earth Mover's Distance under Transformation Sets. In: Proceedings of the International Conference on Computer Vision. Canada, pp. 173--187.
[12]
Fonseca, M. J., and Jorge, J. A. 2003. Indexing High-dimensional Data for Content-based Retrieval in Large Databases. In: Proceedings of the 8th International Conference on Database Systems for Advanced Applications. Japan, pp. 267-274.
[13]
Funkhauser, T., Min, P., Kazhdan, M., Chen, J., Halderman, A., Dobkin, D., and Jacbos, D. 2003. A search engine for 3D models. ACM Transaction on Graphics, Vol. 22, No. 1, pp. 83--105.
[14]
Guttman, A. 1984. R-tree: A dynamic index structure for spatial searching, In: Proceedings of the ACM SIGMOD International Conference on Management of Data. Boston, pp. 47--54.
[15]
Ishikawa, Y., Subramanya, R., and Faloutsos, C. 1998. MindReader: query databases through multiple examples. In: Proceedings of the 24th International Conference on Very Large Data Base. New York, NY, pp. 218--227.
[16]
Jagadish, H. V., Ooi, B. C., Tan, K. L., Yu, C., and Zhang, R. 2005. iDistance: An Adaptive B+-tree Based Indexing Method for Nearest Neighbor Search. ACM Transaction on Data Base Systems, Vol. 30, No. 2, pp. 364--397.
[17]
Kherfi, M. L., Ziou, D., and Bernardi, A. 2002. Learning from negative example in relevance feedback for content-based image retrieval. In: Proceedings of the 16th International Conference on Pattern Recognition. Quebec, Canada, pp. 933--936.
[18]
Liu, F., Zhuang, Y. T., Wu F., and Pan, Y. H. 2003. 3D motion retrieval with motion index tree. Computer Vision and Image Understanding, Vol. 92, No. 2. pp. 265--284.
[19]
Nastar, C., Mitschke, M., and Meilhac, C. 1998. Efficient query refinement for image retrieval. In: Proceedings of the International Conference on Computer Vision and Pattern Recognition. Santa Barbara, CA, pp. 547--552.
[20]
Palmondon, R. and Srihari, S. N. 2000. On-Line and Off-Line hand-writing Recognition: A Comprehensive Survey, IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 22, No. l,pp. 63--84.
[21]
Picard, R. W., Minka, T. P., and Szummer, M. 1996. Modeling user subjectivity in image libraries. In: Proceedings of the International Conference on Image Processing. Lausanne, Switzerland, pp. 777--780.
[22]
Rath, T.M., Kane, S., Lehman, A., Partridge, E. and Manmatha, R. 2002. Indexing for a Digital Library of George Washington's Manuscripts: A Study of Word Matching Techniques, CIIR Technical Report, University of Massachusetts Amherst.
[23]
Rui, Y, Huang, T. S., Oortega, M., Mehrotra, S. 1998. Relevance feedback: A power tool in interactive content-based image retrieval. IEEE Transaction on Circuits and Systems for Video Technology, Vol. 8, No. 5. pp. 644--655.
[24]
Sakurai, Y, Yoshikawa, M., Uemura, S., and Kojima, H. 2000. The A-tree: An index structure for high-dimensional spaces using relative approximation. In: Proceedings of the International Conference on Very Large Data Base. Cairo, pp. 516--526.
[25]
Shi, B. L., Zhang, L., Wang, Y. and Chen, Z. F., 2001, Content Based Chinese Script Retrieval Through Visual Similarity Criteria, Chinese Journal of Software Vol. 12. No. 9, pp. 1336--1342.
[26]
The Cadal Project, http://www.cadal.zju.edu.cn, 2005.
[27]
Tieu, K. and Viola, P. 2000. Boosting image retrieval. In: Proceedings of the International Conference on Computer Vision and Pattern Recognition. Hilton Head, SC, pp. 228--235.
[28]
Vasconcelos, N. and Lippman, A. 2000. Learning from user feedback in image retrieval systems. In: Proceedings of the Advances in Neural Information Processing Systems.
[29]
Weber, R., Schek, H., and Bott, S. 1998. A quantitative analysis and performance study for similarity-search methods in high-dimensional spaces. In: Proceedings of the International Conference on Very Large Data Base. New York. pp. 194--205.
[30]
Wu, Y. S. and Ding, X. Q., 1992. Chinese character recognition: the principles and the implementations. Beijing: Advanced Education Press.
[31]
Yosef, I. B., Kedem, K., Dintstein, I., Beit-Arie, M., and Eengel, E. 2004. Classification of Hebrew Calligraphic Handwriting Styles: Preliminary Results. In: Proceedings of the 1st International Workshop on Document Image Analysis for Library, pp. 299--305.
[32]
Zhang, R. and Zhang, Z. 2004. Stretching Bayesian learning in the relevance feedback of image retrieval. In: Proceedings of the European Conference on Computer Vision. Prague, Czech, pp. 355--367.
[33]
Zhang, T., R. Ramakhrisnan, and Livny, M. 1996. BIRCH: An efficient data clustering method for very large databases. In: Proceedings of the ACM SIGMOD International Conference on Management of Data. Montreal, pp. 103--114.
[34]
Zhang X. Z., 1992. Chinese Character Recognition Techniques. Beijing: Tsinghua University Press.
[35]
Zhou, X. S. and Huang, T. S. 2003. Relevance feedback in image retrieval: a comprehensive review. Multimedia Systems. Vol. 8, No. 6, pp. 536--544.
[36]
Zhou, X., and Huang, T. 2001. Small sample learning during multimedia retrieval using Bias Map. In: Proceedings of the International Conference on Computer Vision and Pattern Recognition. Kauai, HI, pp. 11--17.
[37]
Zhou, Z. H., Chen, K. J., and Dai, H. B. 2006. Enhancing relevance feedback in image retrieval using unlabeled data. ACM Transactions on Information Systems. Vol. 24. No. 2. pp. 219--244.
[38]
Zhuang, Y. T, Zzhang, X. F, Wu, J. Q., and Lu, X. Q. 2004. Retrieval of Chinese Calligraphic Character Image. In: Proceedings of the 5th Pacific-Rim Conference on Multimedia. Beijing, pp. 17--24

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      cover image ACM Transactions on Asian Language Information Processing
      ACM Transactions on Asian Language Information Processing  Volume 6, Issue 2
      September 2007
      84 pages
      ISSN:1530-0226
      EISSN:1558-3430
      DOI:10.1145/1282080
      Issue’s Table of Contents

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 01 September 2007
      Published in TALIP Volume 6, Issue 2

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      Author Tags

      1. Chinese calligraphic character
      2. Hyper-centre relocation
      3. Pseudo k-NN

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      • (2013)Approximate high-dimensional nearest neighbor queries using R-forestsProceedings of the 17th International Database Engineering & Applications Symposium10.1145/2513591.2513652(48-57)Online publication date: 9-Oct-2013
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