Abstract
This paper describes a content-based approach to improve image retrieval effectiveness. First, we define two new measures for computing similarity among images based on color histograms, namely the dissimilitude distance DS* and the similarity distance E. The latter is incorporated into the exponentiation part of the Gibbs distribution and into the generalized Dirichlet mixture, while the former is compared to five similarity measures: L 1, L 2 (Euclidean distance), E as well as Gibbs and Dirichlet distributions integrating the similarity measure E. Then, in order to overcome the limitations (and inappropriateness) of some previous information retrieval measures in evaluating the efficiency of an image retrieval process, three variants of a new effectiveness measure are proposed and experimented on an image collection for different similarity distances.
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© 2004 Springer-Verlag Berlin Heidelberg
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Missaoui, R., Sarifuddin, M., Vaillancourt, J. (2004). An Effective Approach Towards Content-Based Image Retrieval. In: Enser, P., Kompatsiaris, Y., O’Connor, N.E., Smeaton, A.F., Smeulders, A.W.M. (eds) Image and Video Retrieval. CIVR 2004. Lecture Notes in Computer Science, vol 3115. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27814-6_41
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DOI: https://doi.org/10.1007/978-3-540-27814-6_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22539-3
Online ISBN: 978-3-540-27814-6
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