Content Based Image Identification on Cultural Databases

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.