ImageTerrier is a novel easily extensible open-source, scalable, high-performance search engine platform for content-based image retrieval applications. The platform provides a comprehensive test-bed for experimenting with bag-of-visual-words image retrieval techniques. It incorporates a state-of-the-art implementation of the single-pass indexing technique for constructing inverted indexes and is capable of producing highly compressed index data structures. ImageTerrier is written as an extension to the open-source Terrier, "Terabyte Retriever", test-bed platform for textual information retrieval research. The ImageTerrier platform is demonstrated to successfully index and search a corpus of over 10 million images containing just under 10,000,000,000 quantised SIFT visual terms.