Combining local and global visual feature similarity using a text search engine

In this paper we propose a novel approach that allows processing image content based queries expressed as arbitrary combinations of local and global visual features, by using a single index realized as an inverted file. The index was implemented on top of the Lucene retrieval engine. This is particularly useful to allow people to efficiently and interactively check the quality of the retrieval result by exploiting combinations of various features when using content based retrieval systems.