Scalable object-based image retrieval
Digital visual libraries have currently available huge amounts of content in unstructured, non-indexed form. Since these collections keep growing fast, retrieving specific images is becoming extremely difficult. It is too slow to linearly search all the stored feature vectors to find those that satisfy the query criteria. Scalability is crucial for an image retrieval system to be practical and realistic. In this paper a simple hierarchical object descriptor scheme, which is compact, flexible, and inherently suited for hierarchical search, is described. By integrating a suitable segmentation algorithm into the descriptor generation schema, the proposed approach becomes object oriented. Basically, features used for the extraction of image regions belonging to single physical objects are used in the definition of object descriptors. The resulting technique generates compact scalable descriptions for each object in the database. Experimental results show the performance of the presented schema in terms of accuracy and scalability.