The SCHEMA Network of Excellence aims to bring together a critical mass of universities, research centers, industrial partners and end users, in order to design a reference system for content-based semantic scene analysis, interpretation and understanding. In this paper, advances in the development of the SCHEMA reference system are reported, focusing on the application of region-based image retrieval using automatic segmentation. More specifically, the integration of four segmentation algorithms and the MPEG-7 eXperimentation Model with the reference system are discussed, along with the motivation behind these and various other choices that were made during the development of the reference system. Experimental results for this system, as well as results for an earlier version of it employing proprietary descriptors, are shown using a common collection of images. Comparative evaluation of these versions, both in terms of retrieval accuracy and in terms of time-efficiency, allows the evaluation of the reference system as a whole as well as the evaluation of the usability of different components integrated with it, such as the MPEG-7 eXperimentation Model. These results illustrate the efficiency of the proposed system, as well as its suitability in serving as a test-bed for evaluating and comparing different algorithms and approaches pertaining to the content-based and semantic manipulation of visual information.