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Content-based image retrieval systems combine perceptual features such as color, texture and shape with semantic concepts for improving the quality of the query's results. In this paper, an annotation technique that combines color and texture with keywords is presented. A method based on color similarity along with a keyword mining technique is used to propagate keywords extracted from a sub-set of annotated images into a large-scale database. A method based on texture properties is applied to link keywords with regions within the images. Finally, an approach for semantic labeling of images is described. In this approach, accuracy of the annotations is estimated and the relationships among keywords are identified. The presented annotation technique is useful for labeling images with keywords construing the underlying semantic content.