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Fast interactive image retrieval with a real-image presentation interface

We propose an image retrieval system that searches a database for images similar to a target imagined by a user. The system uses query images, image features and estimated distances for searching the database. We discuss three types of user interfaces (UIs), which use synthetic computer graphics, real images, or both, for queries. When UIs use real images, the images must be retrieved from the database for each interaction. This is a time-consuming process with conventional retrieval methods. We therefor used a database structure that had been previously used for a method called “incremental intersection”. In conventional methods, histogram bins for the same image are stored in one group, but in this method, the bins are grouped by color. This means that only the histogram data needed at that moment has to be loaded during image retrieval. As a result, our method drastically reduces the time required for data loading and distance calculation.