A Fuzzy-Rule Based Ontology for Urban Object Recognition

Stella Marc-Zwecker, Khalid Asnoune, Cédric Wemmert


In this paper we outline the principles of a methodology for semi-automatic recognition of urban objects from satellite images. The methodology aims to provide a framework for bridging the semantic gap problem. Its principle consists in linking abstract geographical domain concepts with image segments, by the means of ontologies use. The imprecision of image data and of qualitative rules formulated by experts geographers are handled by fuzzy logic mechanisms. We have defined fuzzy rules, implemented in SWRL (Semantic Web Rule Language), which allow classification of image segments in the ontology. We propose some fuzzy classification strategies, which are compared and evaluated through an experimentation performed on a VHR image of Strasbourg region.


  1. Athanasiadis, T., Mylonas, P., Avrithis, Y., and Kollias, S. (2007). Semantic image segmentation and object labeling. Circuits and Systems for Video Technology, IEEE Transactions on, 17(3):298-312.
  2. Belgiu, M., Lampoltshammer, T. J., Hofer, B., et al. (2013). An Extension of an Ontology-Based Land Cover Designation Approach for Fuzzy Rules, volume 2013. Verlag der O sterreichischen Akademie der Wissenschaften.
  3. Bobillo, F. and Straccia, U. (2010). Fuzzy ontology representation using owl 2. CoRR, abs/1009.3391.
  4. Bouziani, M., Goïta, K., and He, D.-C. (2010). Automatic change detection of buildings in urban environment from very high spatial resolution images using existing geodatabase and prior knowledge. ISPRS Journal of Photogrammetry and Remote Sensing, 65(1):143- 153.
  5. Comaniciu, D. and Meer, P. (2002). Mean shift: A robust approach toward feature space analysis. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 24(5):603-619.
  6. Coradeschi, S. and Saffiotti, A. (2003). An introduction to the anchoring problem. Robotics and Autonomous Systems, 43:85-96.
  7. Cravero, M., de Beuvron, F. d. B., Zanni-Merk, C., and Marc-Zwecker, S. (2012). A description logics geographical ontology for effective semantic analysis of satellite images. In KES, pages 1573-1582.
  8. de Bertrand de Beuvron, F., Marc-Zwecker, S., Puissant, A., and Zanni-Merk, C. (2013). From expert knowledge to formal ontologies for semantic interpretation of the urban environment from satellite images. International Journal of Knowledge-based and Intelligent Engineering Systems, 17(1):55-65.
  9. Dubois, D. and Prade, H. (2006). La logique floue. REE. Revue de l'électricité et de l'électronique, (8):35-41.
  10. Fonseca, F. T., Egenhofer, M. J., Agouris, P., and Caˆmara, G. (2002). Using ontologies for integrated geographic information systems. Transactions in GIS, 6(3):231- 257.
  11. Forestier, G., Puissant, A., Wemmert, C., and Ganc¸arski, P. (2012). Knowledge-based region labeling for remote sensing image interpretation. Computers, Environment and Urban Systems, 36(5):470-480.
  12. Fudholi, D. H., Maneerat, N., Varakulsiripunth, R., and Kato, Y. (2009). Application of protégé, swrl and sqwrl in fuzzy ontology-based menu recommendation. In Intelligent Signal Processing and Communication Systems, 2009. ISPACS 2009. International Symposium on, pages 631-634. IEEE.
  13. Ghorbel, H., Bahri, A., and Bouaziz, R. (2010). Fuzzy ontologies building method: Fuzzy ontomethodology. In Fuzzy Information Processing Society (NAFIPS), 2010 Annual Meeting of the North American.
  14. Grau, B., Horrocks, I., Motik, B., Parsia, B., PatelSchneider, P., and Sattler, U. (2008). Owl 2: The next step for owl. Web Semantics: Science, Services and Agents on the World Wide Web.
  15. Gruber, T. R. (1993). Toward Principles for the Design of Ontologies Used for Knowledge Sharing. Toward Principles for the Design of Ontologies Used for Knowledge Sharing, 43:907-928.
  16. Horrocks, I., Patel-Schneider, P. F., Boley, H., Tabet, S., Grosof, B., and Dean, M. (2004). SWRL: A semantic web rule language combining OWL and RuleML. W3c member submission, World Wide Web Consortium.
  17. Maillot, E. and Thonnat, M. (2008). Ontology based complex object recognition. Image and Vision Computing, 26(1):102-113.
  18. Mamdani, E. H. (1977). Application of fuzzy logic to approximate reasoning using linguistic systems. IEEE Transactions on Computers, 26:1182-1191.
  19. Marc-Zwecker, S., De Beuvron, F. D. B., Zanni-Merk, C., Le Ber, F., et al. (2013). Qualitative spatial reasoning in rcc8 with owl and swrl. In KEOD 2013- International Conference on Knowledge Engineering and Ontology Development.
  20. Sebari, I. and He, D.-C. (2013). Automatic fuzzy objectbased analysis of vhsr images for urban objects extraction. ISPRS Journal of Photogrammetry and Remote Sensing, 79:171-184.
  21. Shackelford, A. K. and Davis, C. H. (2003). A combined fuzzy pixel-based and object-based approach for classification of high-resolution multispectral data over urban areas. IEEE T. Geoscience and Remote Sensing, 41(10):2354-2363.
  22. Smeulders, A., Worring, M., Santini, S., Gupta, A., and Jain, R. (2000). Content-based image retrieval at the end of the early years. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22.
  23. Straccia, U. (2005). A fuzzy description logic for the semantic web.
  24. Sui, D. Z. (1992). A fuzzy gis modeling approach for urban land evaluation. Computers, environment and urban systems, 16(2):101-115.
  25. Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8:338-353.

Paper Citation

in Harvard Style

Marc-Zwecker S., Asnoune K. and Wemmert C. (2014). A Fuzzy-Rule Based Ontology for Urban Object Recognition . In Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2014) ISBN 978-989-758-049-9, pages 153-160. DOI: 10.5220/0005026601530160

in Bibtex Style

author={Stella Marc-Zwecker and Khalid Asnoune and Cédric Wemmert},
title={A Fuzzy-Rule Based Ontology for Urban Object Recognition},
booktitle={Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2014)},

in EndNote Style

JO - Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2014)
TI - A Fuzzy-Rule Based Ontology for Urban Object Recognition
SN - 978-989-758-049-9
AU - Marc-Zwecker S.
AU - Asnoune K.
AU - Wemmert C.
PY - 2014
SP - 153
EP - 160
DO - 10.5220/0005026601530160