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Heritage Preservation pp 143–160Cite as

Ontology-Driven Content-Based Retrieval of Heritage Images

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Abstract

In this paper, we present an approach to retrieve structurally and semantically similar images from heritage image dataset. It is an ontology-driven content-based image retrieval (CBIR) system that follows bag of visual words model to recollect near-similar images from the database. Locality-sensitive hashing (LSH) technique has been employed to determine approximate nearest neighbor. We have used an ontology that is particularly developed for Hindu mythology using standard ontology markup language (OWL) on Protege framework to narrow down the semantic gap in the search space. The inclusion of ontology to prune the search space of CBIR system is observed to provide a considerable improvement in the performance. The approach is tested against annotated databases of heritage images that are collected from various heritage sites across India. A web-based system has also been developed to provide a suitable interface and to demonstrate this technique.

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Notes

  1. 1.

    http://asi.nic.in/asi_monu_alphalist_karnataka_bangalore.asp.

  2. 2.

    http://asi.nic.in/asi_monu_alphalist_andhra.asp.

  3. 3.

    http://asi.nic.in/asi_monu_alphalist_westbengal.asp.

  4. 4.

    This system is hosted in https://viplab.iitkgp.ac.in/smarak/index.jsp.

  5. 5.

    http://www.sit.iitkgp.ernet.in/Meghamala/.

  6. 6.

    System Configuration: 8GB RAM with 2.66 GHz.

References

  1. Angelides, M.C.: Multimedia content modeling and personalization. In: Encyclopedia of Multimedia, pp. 510–515. Springer (2008)

    Google Scholar 

  2. Bay, H., Ess, A., Tuytelaars, T., Van Gool, L.: Speeded-up robust features (SURF). Comput. Vis. Image Underst. 110(3), 346–359 (2008)

    Article  Google Scholar 

  3. Chua, T.-S., Pung, H.-K., Lu, G.-J., Jong, H.-S.: A concept-based image retrieval system. In: Proceedings of the Twenty-Seventh Hawaii International Conference on System Sciences, 1994, vol. 3, pp. 590–598. IEEE (1994)

    Google Scholar 

  4. Datar, M., Immorlica, N., Indyk, P., Mirrokni, V.S.: Locality-sensitive hashing scheme based on p-stable distributions. In: Proceedings of the Twentieth Annual Symposium on Computational Geometry, pp. 253–262. ACM (2004)

    Google Scholar 

  5. Evaluation of ranked retrieval results. http://nlp.stanford.edu/IR-book/html/htmledition/evaluation-of-ranked-retrieval-results-1.html. Accessed 15 July 2016

  6. Gowsikhaa, D., Abirami, S., Baskaran, R.: Construction of image ontology using low-level features for image retrieval. In: 2012 International Conference on Computer Communication and Informatics (ICCCI), pp. 1–7. IEEE (2012)

    Google Scholar 

  7. Gudewar, A.D., Ragha, L.R.: Ontology to improve CBIR system. Int. J. Comput. Appl. 52(21), 23–30 (2012)

    Google Scholar 

  8. Gupta, U., Chaudhury, S.: Deep transfer learning with ontology for image classification. In: 2015 Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG), pp. 1–4 (2015)

    Google Scholar 

  9. Harit, G., Chaudhury, S., Paranjpe,J.: Ontology guided access to document images. In: Proceedings of the Eighth International Conference on Document Analysis and Recognition, pp. 292–296. IEEE (2005)

    Google Scholar 

  10. Horridge, M.: A Practical Guide To Building OWL Ontologies Using The Protege-OWL Plugin and CO-ODE Tools Edition 1.0. The University Of Manchester (2004)

    Google Scholar 

  11. Jégou, H., Douze, M., Schmid, C.: Improving bag-of-features for large scale image search. Int. J. Comput. Vis. 87(3), 316–336 (2010)

    Article  Google Scholar 

  12. Liu, J.: Image retrieval based on bag-of-words model. CoRR. Arxiv:abs/1304.5168 (2013)

  13. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004)

    Article  Google Scholar 

  14. Maji, A.K., Mukhoty, A., Majumdar, A.K., Mukhopadhyay, J., Sural, S., Paul, S., Majumdar, B.: Security analysis and implementation of web-based telemedicine services with a four-tier architecture. In: Second International Conference on Pervasive Computing Technologies for Healthcare, 2008. PervasiveHealth 2008, pp. 46–54 (2008)

    Google Scholar 

  15. Makridis, M., Daras, P.: Automatic classification of archaeological pottery sherds. J. Comput. Cult. Herit. (JOCCH) 5(4), 15 (2012)

    Google Scholar 

  16. Mallik, A., Chaudhury, S., Ghosh, H.: Nrityakosha: preserving the intangible heritage of Indian classical dance. J. Comput. Cult. Herit. (JOCCH) 4(3), 11 (2011)

    Google Scholar 

  17. Mallik, A., Chaudhury, S., Madan, S., Dinesh, T., Chandru, U.V.: Archiving mural paintings using an ontology based approach. In: Asian Conference on Computer Vision, pp. 37–48 (2012)

    Chapter  Google Scholar 

  18. Mallik, A., Ghosh, H., Chaudhury, S., Harit, G.: MOWL: an ontology representation language for web-based multimedia applications. ACM Trans. Multimed. Comput. Commun. Appl. (TOMM) 10(1), 8:1–8:21 (2013)

    Article  Google Scholar 

  19. Mishra, S., Mukherjee, J., Mondal, P., Aswatha, S.M., Mukherjee, J.: Real-time retrieval system for heritage images. In: Emerging Research in Electronics, Computer Science and Technology, pp. 245–253. Springer (2014)

    Google Scholar 

  20. Mukherjee, J., Aswatha, S.M., Mondal, P., Mukherjee, J., Mitra, P.: Duplication detection for image sharing systems. In: Proceedings of the 2014 Indian Conference on Computer Vision Graphics and Image Processing (ICVGIP), pp. 4:1–4:7 (2014)

    Google Scholar 

  21. Mukherjee, J., Mukhopadhyay, J., Mitra, P.: A survey on image retrieval performance of different bag of visual words indexing techniques. In: Proceedings of the IEEE Students’ Technology Symposium (TechSym), pp. 99–104 (2014)

    Google Scholar 

  22. Popescu, A., Millet, C., Moëllic, P.-A.: Ontology driven content based image retrieval. In: Proceedings of the 6th ACM International Conference on Image and Video Retrieval, pp. 387–394. ACM (2007)

    Google Scholar 

  23. Popescu, A., Moëllic, P.-A., Millet, C.: SemRetriev: an ontology driven image retrieval system. In: Proceedings of the 6th ACM International Conference on Image and Video Retrieval, pp. 113–116. ACM (2007)

    Google Scholar 

  24. Prud, E., Seaborne, A., et al.: SPARQL query language for RDF (2006)

    Google Scholar 

  25. Resnik, P., et al.: Semantic similarity in a taxonomy: an information-based measure and its application to problems of ambiguity in natural language. J. Artif. Intell. Res. (JAIR) 11, 95–130 (1999)

    MATH  Google Scholar 

  26. Sivic, J., Zisserman, A.: Video Google: efficient visual search of videos. In: Toward Category-Level Object Recognition, vol. 4170, pp. 127–144. Springer (2006)

    Chapter  Google Scholar 

  27. Styltsvig, H.B.: Ontology-based information retrieval (2006)

    Google Scholar 

  28. Sussna, M.: Word sense disambiguation for free-text indexing using a massive semantic network. In: Proceedings of the Second International Conference on Information and Knowledge Management, pp. 67–74. ACM (1993)

    Google Scholar 

  29. Town, C., Sinclair, D.: Ontological query language for content based image retrieval. In: IEEE Workshop on Content-Based Access of Image and Video Libraries, 2001. (CBAIVL 2001), pp. 75–80. IEEE (2001)

    Google Scholar 

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Acknowledgements

This work is carried out under the sponsorship of Department of Science and Technology, Govt. of India through sanction number NRDMS/11/1586/2009.

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Authors and Affiliations

  1. Visual Information Processing Laboratory, Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, 721302, West Bengal, India

    Dipannita Podder, Jit Mukherjee, Shashaank Mattur Aswatha, Jayanta Mukherjee & Shamik Sural

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  1. Dipannita Podder
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  2. Jit Mukherjee
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  3. Shashaank Mattur Aswatha
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  4. Jayanta Mukherjee
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  5. Shamik Sural
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Correspondence to Dipannita Podder .

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Editors and Affiliations

  1. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, West Bengal, India

    Bhabatosh Chanda

  2. Department of Electrical Engineering, Indian Institute of Technology Bombay, Mumbai, Maharashtra, India

    Subhasis Chaudhuri

  3. CSIR-CEERI, Pilani, Rajasthan, India

    Santanu Chaudhury

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Podder, D., Mukherjee, J., Aswatha, S.M., Mukherjee, J., Sural, S. (2018). Ontology-Driven Content-Based Retrieval of Heritage Images. In: Chanda, B., Chaudhuri, S., Chaudhury, S. (eds) Heritage Preservation. Springer, Singapore. https://doi.org/10.1007/978-981-10-7221-5_8

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  • DOI: https://doi.org/10.1007/978-981-10-7221-5_8

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