Dominant color region based indexing for CBIR

Our world is dominated by visual information and a tremendous amount of such information is being added day-by-day. It would be impossible to cope with this explosion of visual data, unless they are organized such that we can retrieve them efficiently and effectively. The main problem in organizing and managing such visual data is indexing, the assignment of a synthetic descriptor which facilitates its retrieval. It involves extracting relevant entities or characteristics from images as index keys. Then a representation is chosen for the keys and specific meaning is assigned to it. Color is an important cue for content based image retrieval (CBIR) systems. We propose a technique to index and store images based on dominant color regions. Features like region size and location of the region are extracted and used as similarity measures. Images with similar indices are stored as an image cluster in a Hash table. A prototype of the retrieval system is developed using the JAVA language.