An approach to image retrieval using spatial configurations is presented. The goal is to search the database for images that contain similar objects (image-patches) with a given configuration, size and position. The proposed approach consists of creating localized representations robust to segmentation variations, and a sub-graph matching method to compare the query with the database items. Localized object representations are created using a community detection method that groups visually similar segments. Extensive experimental results on three challenging datasets are provided to demonstrate the feasibility of the approach.