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Volume: 4 | Article ID: art00079
Color Emotions for Image Classification and Retrieval
  DOI :  10.2352/CGIV.2008.4.1.art00079  Published OnlineJanuary 2008

Many content-based image retrieval systems are not taking into account high level semantic information. In this paper we describe our attempts to include color-based emotion-related properties of images in the search. We show that using color emotion metrics in content-based image retrieval leads to interesting methods for image retrieval and classification based on semantic concepts. The color emotion metric used is derived from psychophysical experiments and uses three scales: activity, weight and heat. It was originally designed for single-color combinations and later extended to include pairs of colors. We show that a modified approach for statistical analysis of color emotions in images, involving transformations of ordinary RGB-histograms, provides a useful tool for image classification and retrieval. The methods used are both very fast in feature extraction, and descriptor vectors are very short. This is essential in our application where we intend to use it for searching huge image databases containing millions or billions of images.

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Martin Solli, Reiner Lenz, "Color Emotions for Image Classification and Retrievalin Proc. IS&T CGIV 2008/MCS'08 4th European Conf. on Colour in Graphics, Imaging, and Vision 10th Int'l Symp. on Multispectral Colour Science,  2008,  pp 367 - 371,

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