skip to main content
research-article

Efficient Personalized Probabilistic Retrieval of Chinese Calligraphic Manuscript Images in Mobile Cloud Environment

Published: 19 December 2014 Publication History

Abstract

Ancient language manuscripts constitute a key part of the cultural heritage of mankind. As one of the most important languages, Chinese historical calligraphy work has contributed to not only the Chinese cultural heritage but also the world civilization at large, especially for Asia. To support deeper and more convenient appreciation of Chinese calligraphy works, based on our previous work on the probabilistic retrieval of historical Chinese calligraphic character manuscripts repositories, we propose a system framework of the multi-feature-based Chinese calligraphic character images probabilistic retrieval in the mobile cloud network environment, which is called the DPRC. To ensure retrieval efficiency, we further propose four enabling techniques: (1) DRL-based probability propagation, (2) optimal data placement scheme, (3) adaptive data robust transmission algorithm, and (4) index support filtering scheme. Comprehensive experiments are conducted to testify the effectiveness and efficiency of our proposed DPRC method.

References

[1]
Allcocka, B., Bestera, J., Bresnahan, J., et al. 2002. Data management and transfer in high-performance computational grid environments. Parallel Comput. 28, 5, 749--771.
[2]
Amazon EC2. 2009. http://aws.amazon.com/ec2/.
[3]
Asi, A., Rabaev, I., Kedem, K., and Sana, J. El, 2011. User-assisted alignment of arabic historical manuscripts. In Proceedings of the International Workshop on Historical Document Imaging and Processing (HIP’11).
[4]
Belongie, S., Malik, J., and Puzicha, J. 2002. Shape Matching and Object Recognition Using Shape Contexts. IEEE Trans. Pattern Anal. Mach. Intell. 24, 4, 509--522.
[5]
Berchtold, S., Böhm, C., Jagadish, H. V., Kriegel, H.-P., and Sander, J. 2000. Independent quantization: An index compression technique for high-dimensional data spaces. In Proceedings of the International Conference on Data Engineering. 577--588.
[6]
Böhm, C., Berchtold, S., and Keim, D. 2001. Searching in high-dimensional spaces: Index structures for improving the performance of multimedia databases. ACM Comput. Surv. 33, 3, 322--373.
[7]
CADAL. 2010. The CADAL Project. www.cadal.zju.edu.cn.
[8]
Chang, R.-C., Shih, T. K. and Hsu, H.-H. 2008. A strategic decomposition for adaptive image transmission. J. Inf. Sci. Eng. 24, 3, 691--707.
[9]
Chang, C. C., Shine, F. C., and Chen, T. S., 1999. A new scheme of progressive image transmission based on bit-plane method. In Proceedings of the Asia-Pacific Conference on Communications and 4th Optoelectronics and Communications Conference, 2, 892--895.
[10]
Chang, C. C., Shih, T. K., and Lin, I. C., 2002. An efficient progressive image transmission method based on guessing by neighbors. Visual Computer: Int. J. Computer Graph. 18, 341--353.
[11]
Chang, C. C. and Wu, M. N. 2003. A color image progressive transmission method by common bit map block truncation coding approach. In Proceedings of the International Conference on Communication Technology, 2, 1774--1778.
[12]
Charles, J.-T. and Larry, L.-P. 1992. Image transfer: An end-to-end design. In Proceedings of the ACM SIGCOMM Data Communications Festival. 258--268.
[13]
Chui, H. L. and Rangarajan, A. 2003. A new point matching algorithm for non-rigid registration. Comput. Vision Image Understand. 89, 2-3, 114--141.
[14]
Cohen, S. and Guibas, L. 1999. The earth mover’s distance under transformation sets. In Proceedings of the IEEE International Conference on Computer Vision. 173--187.
[15]
Cormen, T. H., Leiserson, C. E., Rivest, R. L., and Stein, C. 2009. Introduction to Algorithms, 3rd Ed. MIT Press.
[16]
Danskin, J.-M., Davis, G.-M., and Song, X.-Y. 1995. Fast lossy internet image transmission. In Proceedings of ACM Multimedia. 321--332.
[17]
Ester, M., Kriegel, H.-P., Sander, J., and Xu, X.-W. 1996. A density-based algorithm for discovering clusters in large spatial databases with noise. In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 226--231.
[18]
Frey, B. J. and Dueck, D. 2007. Clustering by passing messages between data points. Science 315, 972--976.
[19]
Gao, D.-H., Liu, D.-H., Feng, Y.-Q, An, Q. L., and Yu, F. P. 2010. A robust image transmission scheme for wireless channels based on compressive sensing. In Proceedings of the 6th International Conference on Intelligent Computing. Lecture Notes in Computer Science, vol. 6216, 334--341.
[20]
Guttman, A. 1984. R-trees: A dynamic index structure for spatial searching. In Proceedings of the ACM SIGMOD International Conference on Management of Data. 47--57.
[21]
Henrich, A. 1998. The LSDh-Tree: An access structure for feature vectors. In Proceedings of the International Conference on Data Engineering. 362--369.
[22]
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 Trans. Database Syst. 30, 2, 364--397.
[23]
Kim, J. H. and Song, W. J, 1996. Pyramid-structured progressive image transmission using quantization error delivery in transform domains. IEE Proc. Vision Image Signal Process. 143, 132--136.
[24]
Lomet, D. B. and Salzberg, B. 1990. The hB-tree: A multiattribute indexing method with good guaranteed performance. ACM Trans. Database Syst. 15, 4, 625--658.
[25]
Lin, T. and Hao, P. 2005. Compound image compression for real-time computer screen image transmission. IEEE Trans. Image Process. 14, 8, 993--1005.
[26]
Nakagawa, M. and Onuma, M. 2003. On-line handwritten japanese text recognition free from constrains on line direction and character orientation. In Proceedings of the International Conference on Document Analysis and Recognition.
[27]
Pal, U., Jayadevan R., and Sharma, N. 2012. Handwriting Recognition in Indian Regional Scripts: A Survey of Offline Techniques. ACM Trans. Asian Lang. Inform. Process. 11, 1.
[28]
Palmondon, R. and Srihari, S. N. 2000. On-line and off-line hand-writing recognition: A comprehensive survey. IEEE Trans. Pattern Anal. Mach. Intell. 22, 1, 63--84.
[29]
Rabaev, I., Biller, O., El-Sana, J., Kedem, K., and Dinstein, I. 2011. Case study in Hebrew character searching. In Proceedings of the International Conference on Document Analysis and Recognition.
[30]
Raman, S., Balakrishnan, H., and Srinivasan, M. 2000. An image transport protocol for the Internet. In Proceedings of the Annual International Conference on Network Protocols. 209--219.
[31]
Rath, T. M., Manmatha, R., and Lavrenko, V. 2004. A search engine for historical manuscript images. In Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. 369--376.
[32]
Robinson, J. T. 1981. The K-D-B-tree: A search structure for large multidimensional dynamic indexes. In Proceedings of the ACM SIGMOD International Conference on Management of Data. 10--18.
[33]
Ruiz, V. G, Fernández, J.-J., and García, I. 2001. Image compression for progressive transmission. In Proceedings of the19th IASTED International Conference on Applied Informatics: Advances in Computer Applications. 519--524.
[34]
Saabni, R. and Sana, J. El. 2009. Hierarchical On-line Arabic Handwriting Recognition. In Proceedings of the International Conference on Document Analysis and Recognition. 867--871.
[35]
Shi, B. L., Zhang, L., Wang, Y., and Chen, Z. F. 2001. Content Based Chinese Script Retrieval through Visual Similarity Criteria. Chinese J. Software 12, 9, 1336--1342.
[36]
Tzou, K. H. 1987. Progressive image transmission: A review and comparison of techniques. Optical Engin. 26, 581--589.
[37]
Wiki. 2010. http://en.wikipedia.org/wiki/Chinese_calligraphy.
[38]
Wu, Y.-S. and Ding, X. Q. 1992. Chinese character recognition: The principles and the implementations. High Education Press, Beijing.
[39]
Weber, R., Schek, H., and Blott, S. 1998. A quantitative analysis and performance study for similarity-search methods in high-dimensional spaces. In Proceedings of the 24th International Conference on Very Large Data Bases. 194--205.
[40]
Yosef, I. B., Kedem, K., Dinstein, I., Beit-Arie, M., and Engel, E. 2004. Classification of Hebrew calligraphic handwriting styles: Preliminary results. In Proceedings of the 1st International Workshop on Document Image Analysis for Libraries. 299--305.
[41]
Zeng, J. and Liu, Z-Q. 2008. Markov random field-based statistical character structure modeling for handwritten Chinese character recognition. IEEE Trans. Pattern Anal. Mach. Intell. 30, 5, 767--780.
[42]
Zhang, X. Z. 1992. Chinese Character Recognition Techniques. Tsinghua University Press, Beijing.
[43]
Zhou, X. D., Yu, J. L., Liu, C. L., Nagasaki, T., and Marukawa, K. 2007. Online handwritten Japanese character string recognition incorporating geometric context. In Proceedings of the 9th International Conference on Document Analysis and Recognition. 48--52.
[44]
Zhuang, Y., Zhuang, Y-T., Li, Q., and Chen, L. 2007. Interactive high-dimensional index for large Chinese calligraphic character databases. ACM Trans. Asian Lang. Inform. Process. 6, 2.
[45]
Zhuang, Y, Jiang, N, Hu, H, Hu, H-Y, Jiang, G.-C., and Yuan, C-X. 2011. Probabilistic and Interactive Retrieval of Chinese Calligraphic Character Images Based on Multiple Features. In Database Systems for Advanced Applications, Lecture Notes in Computer Science, vol. 6587. 300--310.
[46]
Zhuang, Y-T., Zhang, X-F., Wu, J-Q., and Lu, X-Q. 2005. Retrieval of Chinese calligraphic character image. In Proceedings of the 5th Pacific Rim Conference on Multimedia. 17--24.

Cited By

View all
  • (2023)Adoption of Digital Art NFTs in Hong KongEmerging Technology-Based Services and Systems in Libraries, Educational Institutions, and Non-Profit Organizations10.4018/978-1-6684-8671-9.ch007(151-174)Online publication date: 10-Aug-2023
  • (2023)Towards Effective Crowd-Assisted Similarity Retrieval of Large Cursive Chinese Calligraphic Character ImagesProceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things10.1145/3603781.3603853(403-409)Online publication date: 26-May-2023
  • (2023)Information security and technical issues of cloud storage services: a qualitative study on university students in Hong KongLibrary Hi Tech10.1108/LHT-11-2022-053342:5(1406-1425)Online publication date: 3-Mar-2023
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Transactions on Asian Language Information Processing
ACM Transactions on Asian Language Information Processing  Volume 13, Issue 4
December 2014
84 pages
ISSN:1530-0226
EISSN:1558-3430
DOI:10.1145/2701119
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 December 2014
Accepted: 01 March 2014
Revised: 01 January 2014
Received: 01 November 2013
Published in TALIP Volume 13, Issue 4

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Chinese calligraphic character
  2. probabilistic retrieval
  3. sentiment

Qualifiers

  • Research-article
  • Research
  • Refereed

Funding Sources

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)4
  • Downloads (Last 6 weeks)1
Reflects downloads up to 20 Jan 2025

Other Metrics

Citations

Cited By

View all
  • (2023)Adoption of Digital Art NFTs in Hong KongEmerging Technology-Based Services and Systems in Libraries, Educational Institutions, and Non-Profit Organizations10.4018/978-1-6684-8671-9.ch007(151-174)Online publication date: 10-Aug-2023
  • (2023)Towards Effective Crowd-Assisted Similarity Retrieval of Large Cursive Chinese Calligraphic Character ImagesProceedings of the 2023 4th International Conference on Computing, Networks and Internet of Things10.1145/3603781.3603853(403-409)Online publication date: 26-May-2023
  • (2023)Information security and technical issues of cloud storage services: a qualitative study on university students in Hong KongLibrary Hi Tech10.1108/LHT-11-2022-053342:5(1406-1425)Online publication date: 3-Mar-2023
  • (2019)Visualising and revitalising traditional Chinese martial artsLibrary Hi Tech10.1108/LHT-05-2018-0071Online publication date: 28-Feb-2019

View Options

Login options

Full Access

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media