Summary
As the amount of multimedia data captured and published in Internet constantly grows, it is essential to develop efficient tools for modeling the visual data similarity for browsing and searching in voluminous image databases. Among these methods are those based on compact image representation, such as mixture modeling of the color information conveyed by the images. These methods could be efficient and robust to possible distortions of color information caused by lossy coding. Moreover, they produce a compact image representation in form of a vector of model parameters. Thus, they are well suited for task of a color image retrieval in large, heterogenous databases. This paper focuses on the proper choice of the color space in which the modeling of lossy coded color image information, based on the mixture approximation of chromaticity histogram, is evaluated. Retrieval results obtained when RGB, I1I2I3, YUV , CIE XYZ, CIE L * a * b *, HSx, LSLM and TSL color spaces were employed are presented and discussed.
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Łuszczkiewicz-Piątek, M. (2014). Which Color Space Should Be Chosen for Robust Color Image Retrieval Based on Mixture Modeling. In: S. Choras, R. (eds) Image Processing and Communications Challenges 5. Advances in Intelligent Systems and Computing, vol 233. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-01622-1_7
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DOI: https://doi.org/10.1007/978-3-319-01622-1_7
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