In this paper

a novel approach to semantic concept detection based on local color spatial feature is proposed. There is much noise and redundant information in many global features of color

texture and shape. This local color spatial feature contains more semantic contents of image than other global features by using prior knowledge of semantic concept level to reduce feature dimensions. Experiment results are reported and presented to demonstrate the effectiveness and efficiency of the proposed approach. Average precision of image retrieval by using the semantic concept detection method based on local color spatial feature is 364% higher than the method based on global color feature.