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The Web provides an increasingly powerful and popular publication mechanism. Web documents often contain a large number of images that serve various purposes. Identifying the functional categories of these images is an important task in Web repurposing. This article describes a study on the functional categorization of Web images using data collected from news Web sites. As the popularity of the Web soars, the content on the Web is increasingly accessed from wireless devices that have small screens and different bandwidths. Because many Web documents contain a large number of images serving different purposes, how to identify the function of each image so that it can be handled accordingly is an important issue in Web content repurposing. Much work remains to be done in function-based image classification of all images. Icons that appear regularly on Web sites (for example, newspaper logos) could be classified by analyzing different editions of the pages for repetitions. For the host class, a combination of detecting repetitive images and face recognition should help significantly.