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We present an implementation of NeTra, a prototype image retrieval system that uses color texture, shape and spatial location information in segmented image database. A distinguishing aspect of this system is its incorporation of a robust automated image segmentation algorithm that allows object or region based search. Image segmentation significantly improves the quality of image retrieval when images contain multiple complex objects. Other important components of the system include an efficient color representation, and indexing of color, texture, and shape features for fast search and retrieval. This representation allows the user to compose interesting queries such as "retrieve all images that contain regions that have the color of object A, texture of object B, shape of object C, and lie in the upper one-third of the image" where the individual objects could be regions belonging to different images.
Ma et al. (Fri,) studied this question.