The retrieval of images from image databases: trademarks

Abstract

This paper focuses on the problem of information retrieval from databases containing images rather than text. We propose an error-tolerant alternative to menus and keywords—the feature-matching approach—in which users describe what they want to retrieve in response to a set of queries. The system matches the user's description with descriptions of images already in the database. Database images are then presented to the user in order of similarity to the user's description. The present paper serves four purposes: application of our feature-matching approach to a new image domain (trademarks); systematization of the process for developing these systems (articulation of five stages in the process of system development); specification of criteria for selecting features to maximize system performance; and introduction of concepts of power of discrimination and error tolerance to show how measures of these two factors can be used for evaluating system performance and optimizing system development. Evaluation of the system (including experiments on a small pilot database of trademarks and simulations of large databases) show the proposed set of 150 features would, without modification, be capable of handling expansion of the database to over 50 000 trademarks while still retrieving the target within the first 10 items on average. Analysis suggested several changes that should further improve the feature set.