Abstract

As network connectivity has continued its explosive growth and as storage devices have become smaller, faster, and less expensive, the number of online digitized images has increased rapidly. Successful queries on large, heterogeneous image collections cannot rely on the use of text matching alone. In this paper we describe how we use image analysis in conjunction with an object relational database to provide both textual and content-based queries on a very large collection of digital images. We discuss the e ects of feature computation, retrieval speed, and development issues on our feature storage strategy. 1

Citations