Nowadays, with the ease of use and effectiveness of image manipulation software, combined with the large number of photos published on the Internet, falsification and alteration of existing images are increasingly widespread operations. The task of searching for images which have undergone different types of alterations in a large data collection is called near duplicate detection and is now being applied in a growing number of areas such as plagiarism, fraud prevention and forensic image identification. However, the study of algorithms that allow an ever more precise and efficient search for near duplicates is not always possible because of the scarcity of appropriately annotated benchmark collection.