Cultural institutions are often asked to perform the identification of images in newspapers, thesis and even postcards, where the references are too summary, missing or incorrect - in those cases, the visual data is the only reliable evidence for the identification. Image identification is challenging, because of the transformations the query image may have suffered: which include cropping, rotations, scale changes, etc. In this work we describe an automatic, content-based, system for image identification based on local descriptors. The indexing scheme we have developed allows the use of those descriptors without the long processing times normally associated to them.