Aiming at overcoming the semantic gap between low-level features and high-level semantic concepts of images and to improve the precision of image classification

we propose an approach to construct a color semantic feature to map low-level features to semantically meaningful categories. Color features are extracted first and then a semantic network containing a set of color concepts and related objects is build. Finally

a color semantic 3-tuple is being constructed.The proposed method can not only get better results in image classification

but is also more robust.