Abstract
In this paper, a novel low level feature for content based image retrieval is presented. The proposed feature structure combines color and spatial color distribution information. The combination of these two features in one vector classifies the proposed descriptor to the family of Composite Descriptors. In order to extract the color information, a fuzzy system is being used, which is mapping the number of colors that are included in the image into a custom palette of 8 colors. The way by which the vector of the proposed descriptor is being formed, describes the color spatial information contained in images. To be applicable in the design of large image databases, the proposed descriptor is compact, requiring only 48 bytes per image. Experiments presented in this paper demonstrate the effectiveness of the proposed technique especially for Hand-Drawn Sketches.
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Chatzichristofis, S.A., Boutalis, Y.S., Lux, M. (2011). Combining Color and Spatial Color Distribution Information in a Fuzzy Rule Based Compact Composite Descriptor. In: Filipe, J., Fred, A., Sharp, B. (eds) Agents and Artificial Intelligence. ICAART 2010. Communications in Computer and Information Science, vol 129. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19890-8_4
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DOI: https://doi.org/10.1007/978-3-642-19890-8_4
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