Robson Barcellos,  Rogério Saranz Oliani,  Luciana Lorenzi,  Adilson Gonzaga. 

Color auto-correlograms have been shown to excel color histograms, color coherence vectors and color co-occurrence matrices when used as feature vectors in content based image retrieval (CBIR) systems. This is due mainly to their ability to detect the spatial relation of colors. In this work we show that further improvement in the performance of auto-correlograms can be achieved by choosing an appropriate color space. Specifically, when robustness to illumination condition changes is an issue, HSV color space has been proven to be a good choice to work with.

http://www.lbd.dcc.ufmg.br/colecoes/wvc/2005/0020.pdf

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