This paper deals with efficient retrieval of images from large databases based on the color and shape content in images. With the increasing popularity of the use of large-volume image databases in various applications, it becomes imperative to build an automatic and efficient retrieval system to browse through the entire database. Techniques using textual attributes for annotations are limited in their applications. Our approach relies on image features that exploit visual cues such as color and shape. Unlike previous approaches which concentrate on extracting a single concise feature, our technique combines features that represent both the color and shape in images. Experimental results on a database of 400 trademark images show that an integrated color- and shape-based feature representation results in 99% of the images being retrieved within the top two positions. Additional results demonstrate that a combination of clustering and a branch and bound-based matching scheme aids in improving the speed of the retrievals.