This paper examines the problem of image retrieval from large, heterogeneous image databases. We present a technique that fulfills several needs identified by surveying recent research in the field. This technique fairly integrates a diverse and expandable set of image properties (for example, color, texture, and location) in a retrieval framework, and allows end-users substantial control over their use. We propose a novel set of evaluation methods in addition to applying established tests for image retrieval; our technique proves competitive with state-of-the-art methods in these tests and does better on certain tasks. Furthermore, it improves on many standard image retrieval algorithms by supporting queries based on subsections of images. For certain queries this capability significantly increases the relevance of the images retrieved, and further expands the user’s control over the retrieval process
