In this paper a region-based color image indexing and retrieval algorithm is presented. As a basis for the indexing, a novel K-Means segmentation algorithm is used, modified so as to take into account the coherence of the regions. A new color distance is also defined for this algorithm. Based on the extracted regions, characteristic features are estimated using color, texture and shape information. An important and unique aspect of the algorithm is that, in the context of similarity-based querying, the user is allowed to view the internal representation of the submitted image and the query results. Experimental results demonstrate the performance of the algorithm. The development of an intelligent image content-based search engine for the World Wide Web is also presented, as a direct application of the presented algorithm.