We present a novel region segmentation framework, dedicated to region queries in content-based image retrieval. Some of the features that are considered for image indexing are used for segmenting the image in a few regions of interest. The novelty of our technique comes from the unification of the feature-space and the image-space segmentation in a common framework. The method uses no prior modeling of the image, focusing on local feature distributions and their spatial stability in a multi-feature, multi-resolution approach. Several experiments are presented on real-world imagery, demonstrating the power of the method for segmentation and region queries in image databases.