Many areas of commerce, government, academia, and hospitals create large collections of digital images . Digital image databases open the way to content-based searching. One of the tool that is essential for electronic publishing is a powerful image retrieval system. Most commercial image retrieval systems associate keywords or text with each image and require the user to enter a keyword or textual description of the image. This text based approach is incompetent as some features are nearly impossible to describe with text. In an effort to overcome these problems and to improve image retrieval performance researchers are focusing on content based image retrieval (CBIR). In CBIR retrieval is accomplished by comparing image features directly rather than textual descriptions of image features. Features that are commonly used in CBIR include Color, Texture, Shape and Edges. These features are primitive image descriptors in content based image retrieval systems. Among these features, color feature is the most widely used features for image retrieval because color is the most intuitive feature and can be extracted from images conveniently. In this paper we survey some technical aspects of current content-based image retrieval systems using Color as a feature.