Towards Visual Vocabulary and Ontology-based Image Retrieval System

Jalila Filali, Hajer Baazaoui Zghal, Jean Martinet

2016

Abstract

Several approaches have been introduced in image retrieval field. However, many limitations, such as the semantic gap, still exist. As our motivation is to improve image retrieval accuracy, this paper presents an image retrieval system based on visual vocabulary and ontology. We propose, for every query image, to build visual vocabulary and ontology based on images annotations. Image retrieval process is performed by integrating both visual and semantic features and similarities.

References

  1. Allani, O., Mellouli, N., Baazaoui-Zghal, H., Akdag, H., and Ben-Ghzala, H. (2014). A pattern-based system for image retrieval. In The International Conference on Knowledge Engineering and Ontology Development.
  2. Cho, H., Hadjiiski, L., Sahiner, B., and Helvie, M. (2011). Similarity evaluation in a content-based image retrieval (cbir) cadx system for characterization of breast masses on ultrasound images. Medical Physics, The International Journal of Medical Physics Reserach and Practice.
  3. Deselaers, T. and Ferrari, V. (2011). Visual and semantic similarity in imagenet. In Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on, pages 1777-1784. IEEE.
  4. Hliaoutakis, A., Varelas, G., Voutsakis, E., E.Petrakis, and E.Milios (2006). Information retrieval by semantic similarity. International Journal on Semantic Web and Information Systems, 2:55-73.
  5. Hyvönen, E., Saarela, S., Samppa, Styrman, A., and K.Viljanen (2003). Ontology-based image retrieval. In WWW (Posters).
  6. Jurie, F. and Triggs, B. (2005). Creating efficient codebooks for visual recognition. In Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on, volume 1, pages 604-610. IEEE.
  7. Kurtz, C. and Rubin, D. (2014). Using ontological relationships for comparing images describing by semantic annotations. In EGC 2014, vol. RNTI-E-26, pp.609- 614, pages 609-614.
  8. Martinet, J. (2014). From text vocabularies to visual vocabularies: what basis? In 9e International Conference on Computer Vision Theory and Applications (VISAPP),pp. 668-675, January 2014, Lisbon, Portugal.
  9. Patwardhan, S. and Pedersen, T. (2006). Using wordnetbased context vectors to estimate the semantic relatedness of concepts. In EACL 2006 Workshop on Making Sense of Sense: Bringing Computational Linguistics and Psycholinguistics Together, pages 18.
  10. Sarwara, S., Qayyuma, Z., and Majeedb, S. (2013). Ontology based image retrieval framework using qualitative semanticimage descriptions. In 17th International Conference in Knowledge Based and Intelligent Information and Engineering Systems -KES2013, page 285 294. Procedia Computer Science 22.
  11. Sivic, J. and Zisserman, A. (2003). Video google: A text retrieval approach to object matching in videos. In Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on., pages 1470-1477. IEEE.
  12. Zhang, D. and Lu, G. (2003). Evaluation of similarity measurement for image retrieval. In Neural Networks and Signal Processing, Proceedings of the 2003 International Conference on (Vol. 2, pp. 928-931). IEEE.
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Paper Citation


in Harvard Style

Filali J., Zghal H. and Martinet J. (2016). Towards Visual Vocabulary and Ontology-based Image Retrieval System . In Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-172-4, pages 560-565. DOI: 10.5220/0005832805600565


in Bibtex Style

@conference{icaart16,
author={Jalila Filali and Hajer Baazaoui Zghal and Jean Martinet},
title={Towards Visual Vocabulary and Ontology-based Image Retrieval System},
booktitle={Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2016},
pages={560-565},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005832805600565},
isbn={978-989-758-172-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Towards Visual Vocabulary and Ontology-based Image Retrieval System
SN - 978-989-758-172-4
AU - Filali J.
AU - Zghal H.
AU - Martinet J.
PY - 2016
SP - 560
EP - 565
DO - 10.5220/0005832805600565