Organizing WWW images based on the analysis of page layout and Web link structure

Due to the rapid growth of the number of digital images on the Web, there is an increasing demand for an effective and efficient method of organizing and retrieving the images available. This paper describes a method for clustering and embedding WWW images. By using a vision-based page segmentation algorithm, a Web page is partitioned into blocks, and the textual and link information of an image can be accurately extracted from the block containing that image. By extracting the page-to-block, block-to-image, block-to-page relationships through a link structure and page layout analysis, we construct an image graph. With the image graph model, we use techniques from spectral graph theory for image clustering and embedding. Some experimental results are given in the paper.