Abstract
We propose in this paper to integrate the semantic description of the image and the relational characterization of its components through an architecture which follows a sharp process for generating image index and query representations and computing their correspondence. This architecture relies on an expressive representation formalism handling high-level image descriptions and a conceptual query framework in an attempt to operate image indexing and retrieval operations beyond keyword-based and loosely-coupled state-of-the-art systems. At the experimental level, we evaluate its retrieval performance through recall and precision indicators on a test collection of 2500 color photographs.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Belkhatir, M.: A Full-Text Framework for the Image Retrieval Signal/Semantic Integration. In: Andersen, K.V., Debenham, J., Wagner, R. (eds.) DEXA 2005. LNCS, vol. 3588, pp. 113–123. Springer, Heidelberg (2005)
Belkhatir, M.: On the Signal/Semantic Integration for Symbolic Image Indexing and Retrieval. PhD Thesis of the Joseph Fourier University (2005)
Cohn, A., et al.: Qualitative Spatial Representation and Reasoning with the Region Connection Calculus. Geoinformatica 1, 1–44 (1997)
Egenhofer, M.: Reasoning about binary topological relations. In: Proceedings of SSD, pp. 143–160 (1991)
Hollink, L., et al.: Classification of user image descriptions. Int. Journal of Human Computer Studies 61(5), 601–626 (2004)
Jeon, J., et al.: Automatic image annotation and retrieval using cross-media relevance models. In: Proceedings of ACM SIGIR, pp. 119–126 (2003)
Lim, J.H., Jin, J.S.: A structured learning framework for content-based image indexing and visual query. Multimedia Systems 10(4), 317–331 (2005)
Lu, Y., et al.: A unified framework for semantics and feature based relevance feedback in image retrieval systems. In: Proceedings of ACM Multimedia, pp. 31–37 (2000)
Mechkour, M.: EMIR2: An Extended Model for Image Representation and Retrieval. In: Revell, N., Tjoa, A.M. (eds.) DEXA 1995. LNCS, vol. 978, pp. 395–404. Springer, Heidelberg (1995)
Mojsilovic, A., Rogowitz, B.: Capturing image semantics with low-level descriptors. In: Proceedings of IEEE ICIP, pp. 18–21 (2001)
Ounis, I., Pasca, M.: RELIEF: Combining expressiveness and rapidity into a single system. In: Proceedings of ACM SIGIR, pp. 266–274 (1998)
Sowa, J.F.: Conceptual structures: information processing in mind and machine. Addison-Wesley publishing company, Reading (1984)
Zhou, X.S., Huang, T.S.: Unifying Keywords and Visual Contents in Image Retrieval. IEEE Multimedia 9(2), 23–33 (2002)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Belkhatir, M. (2007). Graph-Based Indexing and Querying on Image Corpora with Unified Visual Semantic and Relational Descriptions. In: Goh, D.HL., Cao, T.H., Sølvberg, I.T., Rasmussen, E. (eds) Asian Digital Libraries. Looking Back 10 Years and Forging New Frontiers. ICADL 2007. Lecture Notes in Computer Science, vol 4822. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77094-7_28
Download citation
DOI: https://doi.org/10.1007/978-3-540-77094-7_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77093-0
Online ISBN: 978-3-540-77094-7
eBook Packages: Computer ScienceComputer Science (R0)