Crawling, indexing, and similarity searching images on the web

Abstract. In this paper, we report on our experience in building an experimental similarity search system on a test collection of more than 50 million images, to show the possibility to scale Content-based Image Retrieval (CBIR) systems towards the Web size. First, we had to tackle the non-trivial process of image crawling and descriptive feature extrac-tion, performed by using the European EGEE computer GRID, building a test collection, the first of such scale, that will be opened to the re-search community for experiments and comparisons. Then, we had to develop indexing and searching mechanisms which can scale up to these volumes and answer similarity queries in real-time. The results of our experiments are very encouraging for future applications.