With the emergence of web albums such as Flickr.com or Picasa.com, the amount of personal image collections administered on the web has increased dramatically. As a consequence, efficient storing, indexing and retrieval techniques are needed. Peer–to–peer (P2P) networks are an interesting solution to maintain large image collections. When performing a query on certain types of P2P networks, source selection is very important. In our scenario, compact summaries of each peer’s image collection, which are known to other peers, are used to determine the most promising peers for a given query. These summaries have to address (1) date and time information, (2) textual information, (3) geolocations and (4) contend–based image features. The present paper outlines a large–scale image retrieval system, relying on data summaries and source selection strategies. While our scenario is based on a P2P system, we also describe how results can be transferred to other application domains such as distributed information retrieval (distributed IR) or tree-based index structures.