Skip to main content
SpringerLink
Log in

Utilising semantic technologies for intelligent indexing and retrieval of digital images

  • Published:
Computing Aims and scope Submit manuscript

Abstract

The proliferation of digital media has led to a huge interest in classifying and indexing media objects for generic search and usage. In particular, we are witnessing a colossal growth in digital image repositories that are difficult to navigate using free-text search mechanisms, which often return inaccurate matches as they in principle rely on statistical analysis of query keyword recurrence in the image annotation or surrounding text. In this paper we present a semantically-enabled image annotation and retrieval engine that is designed to satisfy the requirements of the commercial image collections market in terms of both accuracy and efficiency of the retrieval process. Our search engine relies on methodically structured ontologies for image annotation, thus allowing for more intelligent reasoning about the image content and subsequently obtaining a more accurate set of results and a richer set of alternatives matchmaking the original query. We also show how our well-analysed and designed domain ontology contributes to the implicit expansion of user queries as well as the exploitation of lexical databases for explicit semantic-based query expansion.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Notes

  1. http://www.pressassociation.com/Images/.

  2. http://www.aktors.org/ontology/support#.

References

  1. Buitelaar P, Ramaka S (2005) Unsupervised ontology-based semantic tagging for knowledge markup. In: Proceedings of the workshop on learning in web search at the international conference on machine learning

  2. Bhogal J, Macfarlane A, Smith P (2007) A review of ontology based query expansion. Inform Process Manag Int J 43(4):866–886

    Article  Google Scholar 

  3. Carroll J et al. (2004) Jena: implementing the semantic web recommendations. In: Proceedings of the 13th international world wide web conference. New York, USA, pp 74–83

  4. Ching-man Au Y, Gibbins N, Shadbolt N (2008) A k-nearest-neighbour method for classifying web search results with data in folksonomies. Web intelligence and intelligent agent technology, 2008. International conference on WI-IAT’08. IEEE/WIC/ACM , vol 1. IEEE

  5. Datta R, Joshi D, Li J, Wang JZ (2008) Image retrieval: ideas, influences, and trends of the new age. ACM Comput Surv 40(2):1–60

    Article  Google Scholar 

  6. Fellbau C (1998) WordNet—an electronic lexical database. The MIT press, Cambridge

    Google Scholar 

  7. Frkovic F, Podobnik V, Trzec K, Jezic, G (2008) Agent-based user personalization using context-aware semantic reasoning. In: 12th international conference on knowledge-based intelligent information and engineering systems, pp 166–73

  8. Fuji A, Ishikawa T (2005) Toward the automatic compilation of multimedia encyclopaedias: association images with term descriptions on the web. In: Proceedings of the 2005 international conference on web intelligence, pp 536–542

  9. Gaihua F et al (2005) Ontology-based spatial query expansion in information retrieval. Lect Notes Comput Sci 3761/2005:1466–1482

    Google Scholar 

  10. Hare JS, Lewis PH, Enser PGB, Sandom CJ (2006) Mind the gap: another look at the problem of the semantic gap in image retrieval. In: Proceedings multimedia content analysis, management and retrieval 2006, 607309 – 1. http://eprints.soton.ac.uk/261887/

  11. Haubold A, Natsev A, Naphade M (2006) Semantic multimedia retrieval using lexical query expansion and model-based reranking. In: IEEE International Conference on Multimedia and Expo, pp 1761–1764

  12. Hollink L et al. (2003) Semantic annotation of image collections. In: Workshop on knowledge markup and semantic annotation

  13. Jeon J et al. (2003) Automatic image annotation and retrieval using cross-media relevance models. In: Proceedings of the 26th annual international ACM SIGIR conference on research and development in information retrieval

  14. Lam T, Singh R (2006) Semantically relevant image retrieval by combining image and linguistic analysis. In: Proceedings of the international symposium on visual computing, pp 1686–1695

  15. Lee C, Geunbae G (2005) Probabilistic information retrieval model for a dependency structured indexing system. Int J Inform Process Manage 41(2):161–175

    Article  MATH  Google Scholar 

  16. Maedche A, Motik B, Stojanovic L (2003) Managing multiple and distributed ontologies on the Semantic Web. Int J Very Large Data Bases 12(4):286–302

    Google Scholar 

  17. Noy N, Tu S (2003) The evolution of Protégé-2000: an environment for knowledge-based systems development. In J Human-Comput Stud 58(1):89–123

    Article  Google Scholar 

  18. Osman T, Thakker D, Al-Dabass D (2006) Semantic-driven matchmaking of web services using case-based reasoning. In: IEEE international conference on web services (ICWS’06), September 2006, pp 29–36

  19. Park Y, Li Y (2007) Semantic analysis for topical segmentation of videos. International conference on semantic computing, pp 161–168

  20. Rector A (2003) Modularisation of domain ontologies implemented in description logics and related formalisms including OWL. In: Proceedings of the 2nd international conference on knowledge capture, pp 121–128

  21. Shadbolt N, Berners-Lee T, Hall W (2006) The semantic web revisited. IEEE Intell Syst 21(3):96–101

    Article  Google Scholar 

  22. Smeulders A, Worring M, Santini S, Gupta A, Jain R (2000) Content-based image retrieval at the end of the early years. IEEE Trans Pattern Anal Mach Intell 22(12):1249–1380

    Google Scholar 

  23. Vogel J, Schiele B (2007) Semantic modeling of natural scenes for content-based image retrieval. Int J Comput Vis 72(2):133–157 (2007)

    Article  Google Scholar 

  24. W3C Corporation [online] (2004) OWL web ontology language overview. http://www.w3.org/TR/owl-features

  25. Wang H, Liu, Chia L (2006) Does ontology help in image retrieval? A comparison between keyword, text ontology and multi-modality ontology approaches. In: Proceedings of the 14th annual ACM international conference on multimedia, pp 109–112

  26. Wu K, Yap K (2006) Fuzzy SVM for content-based image retrieval: a pseudo-label support vector machine framework. IEEE Comput Intell Mag 1(2):10–16 May 2006

    Article  Google Scholar 

  27. Yee K et al. (2003) Facated meta data for image search and browsing. In: Proceedings of the SIGCHI conference on human factors in computing systems, pp 401–408

  28. Ying L et al (2007) A survey of content-based image retrieval with high-level semantics. Pattern Recogn 40(1):262–282

    Article  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Computing and Informatics, Nottingham Trent University, Nottingham, UK

    Taha Osman

  2. School of Computing, University of Leeds, Leeds, UK

    Dhavalkumar Thakker

  3. Department of Computer Science, Loughborough University, Loughborough, UK

    Gerald Schaefer

Authors
  1. Taha Osman
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dhavalkumar Thakker
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Gerald Schaefer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Gerald Schaefer.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Osman, T., Thakker, D. & Schaefer, G. Utilising semantic technologies for intelligent indexing and retrieval of digital images. Computing 96, 651–668 (2014). https://doi.org/10.1007/s00607-013-0350-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00607-013-0350-0

Keywords

Mathematics Subject Classification

Search

Navigation