Ontology-based Image Representation

Artur Stepchenko, Arkady Borisov

Abstract


This article presents an overview of ontology based digital image representation. An ontology is a specification of a conceptualization to create a vocabulary for exchanging information, where conceptualization mean a mapping between symbols used in the computer (i.e., the vocabulary) and objects and relations in the real world. In this paper, digital image semantic annotation by ontology and a novel ontological approach that formalizes concepts and relations with respect to image representations for data mining – the Image Representations Ontology (IROn) – are examined.

Keywords:
Digital image; IROn; ontology

Full Text:

 PDF

References


R. A. Moreno, M. d. S. Rebelo and M. A. Gutierrez, “Representation and Indexing of Medical Images,” Anales de Documentación, vol. 14, no. 2, pp. 1–18, 2011. [Online]. Available: Dialnet, http://dialnet.unirioja.es. [Accessed Aug. 1, 2014].

R. Clouard, A. Renouf and M. Revenu, “An Ontology-Based Model for Representing Image Processing Application Objectives,” International Journal of Pattern Recognition and Artificial Intelligence, vol. 24, no. 8, pp. 1181–1208, Dec. 2010. [Online]. Available: World Scientific, http://www.worldscientific.com/. [Accessed August 5, 2014]. http://dx.doi.org/10.1142/S0218001410008354

D. K. Iakovidis, D. Schober, M. Boeker and S. Schulz, “An Ontology of Image Representations for Medical Image Mining,” 9th International Conference: Information Technology and Applications in Biomedicine, pp. 1–4, Nov. 4–7, 2009. [Online]. Available: DebugIT, http://debugit.eu/. [Accessed August 10, 2014].

B. Smith, “Image Ontology.” [Online]. Available: The National Center for Biomedical Ontology, http://www.bioontology.org/. [Accessed Aug. 21, 2014].

N. Magesh and P. Thangaraj, “Image Ontology Construction using Spatial and Temporal Relationships,” Life Science Journal, vol. 10, no. 3, pp. 1–9, 2013. [Online]. Available: Life Sciences, http://www.lifesciencesite.com/. [Accessed Sep. 27, 2014].

R. O. Santos, “Ontology-Based Topological Representation of Remote Sensing Images,” International Journal of Remote Sensing, vol. 35, no. 1, pp. 16–28, 2014. [Online]. Available: Taylor & Francis Online, http://www.tandfonline.com/. [Accessed Sep. 28, 2014]. http://dx.doi.org/10.1080/01431161.2013.858847

D. Lu, M. Batistella and E. Moran, “Integration of Landsat TM and SPOT HRG Images for Vegetation Change Detection in the Brazilian Amazon, “ Photogrammetric Engineering & Remote Sensing, vol. 74, no. 4, pp. 421–430, Apr. 2008. [Online]. Available: ASPRS, http://www.asprs.org/. [Accessed Aug. 3, 2014]. http://dx.doi.org/10.14358/PERS.74.4.421

F. T. Fonseca, M. J. Egenhofer and P. Agouris, “Using Ontologies for Integrated Geographic Information Systems, “ Transactions in GIS, vol. 6, no. 3, pp. 231–257, June 2002. [Online]. Available: Wiley Online Library, http://onlinelibrary.wiley.com. [Accessed Aug. 7, 2014]. http://dx.doi.org/10.1111/1467-9671.00109

D. Li, K. Di and D. Li, “Land Use Classification of Remote Sensing Image with GIS Data Based on Spatial Data Mining Techniques, “ XIXth ISPRS Congress Technical Commission III: Systems for Data Processing, Analysis and Representation, pp. 238–245, Amsterdam, The Neatherlands, July 16–23, 2000. [Online]. Available: ISPRS, http://www.isprs.org/. [Accessed Aug. 8, 2014].

D. Kohli, R. Sliuzas, N. Kerle and A. Stein, “An Ontology of Slums for Image-Based Classification,” Computers, Environment and Urban Systems, vol. 36, no. 2, pp. 154–163, Mar. 2012. [Online]. Available: ResearchGate, http://www.researchgate.net. [Accessed Aug. 12, 2014].

S. Mhiri, S. Despres and E. Zagrouba, “Ontologies for the Semantic- Based Medical Image Indexing: An Overview, “ Proceedings of the 2008 International Conference on Information & Knowledge Engineering, Las Vegas, Nevada, USA, July 14–17, 2008. [Online]. Available: ResearchGate, http://www.researchgate.net. [Accessed Sep. 15, 2014].

M. Tsiknakis, M. Brochhausen, J. Nabrzysky, J. Pucacki, S. G. Sfaikanakis, G. Potamias, C. Desmedt and D. Kafetzopoulos, “A Semantic Grid Infrastructure Enabling Integrated Access and Analysis of Multilevel Biomedical Data in Support of Postgenomic Clinical Trials on Cancer,” IEEE Transactions on Information Technology in Biomedicine, vol. 12, no. 2, pp. 205–217, Mar. 2008. [Online]. Available: IMBB, http://www.imbb.forth.gr. [Accessed Sep. 20, 2014]. http://dx.doi.org/10.1109/TITB.2007.903519


Refbacks

  • There are currently no refbacks.


Copyright (c) 2014 Artur Stepchenko, Arkady Borisov

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.