Discovery of Image Versions in Large Collections

Image collections may contain multiple copies, versions, and fragments of the same image. Storage or retrieval of such duplicates and near-duplicates may be unnecessary and, in the context of collections derived from the web, their presence may represent infringements of copyright. However, identifying image versions is a challenging problem, as they can be subject to a wide range of digital alterations, and is potentially costly as the number of image pairs to be considered is quadratic in collection size. In this paper, we propose a method for finding the pairs of near-duplicates based on manipulation of an image index. Our approach is an adaptation of a robust object recognition technique and a near-duplicate document detection algorithm to this application domain. We show that this method requires only moderate computing resources, and is highly effective at identifying pairs of near-duplicates.