A new intersection tree for content-based image retrieval

Retrieval of images based on their contents is a process that requires comparisons of a given query (image) with virtually all the images stored in a database with respect to a given distance function. But this is inapplicable on large databases. The main difficulties and goals are to focus the search on as few images as possible and to further limit the need to compute extensive distances between them. Here, we introduce a variant of a metric tree data structure for indexing and querying such data. Both a sequential and a parallel versions are introduced. The efficiency of our proposal is studied through experiments on real-world datasets.