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Constraint-based feature indexing and retrieval for image databases

This paper presents a prototype system which uses constraints (mathematical feature mapping functions) to index and retrieve images. Information is automatically extracted from images such as the shape, texture, and position of objects within the image. Once extracted, this feature information is stored in an associatively accessible database. The database allows users to locate images containing objects of interest, or locate objects of interest within images. The system presented here also provides a method for automatic indexing of the database through the learning and application of object types or classes. Query of the database is accomplished by way of: (1) sketched example, (2) selected prototype object from an image or atlas, (3) graphically specified single or multidimensional feature ranges, or (4) class type. The use of pre-derived features and mapping functions allow this method to be efficiently implemented in real-time systems.