文档介绍：1 Content-based Image Retrieval (CBIR) Searching a large database for images that match a query: What kinds of databases? What kinds of queries? What constitutes a match? How do we make such searches efficient? Applications Art Collections . Fine Arts Museum of San Francisco Medical Image Databases CT, MRI, Ultrasound, The Visible Human Scientific Databases . Earth Sciences General Image Collections for Licensing Corbis, Getty Images The World Wide Web What is a query? an image you already have a rough sketch you draw a symbolic description of what you want . an image of a man and a woman on a beach SYSTEMS Some Systems You Can Try Corbis Stock Photography and Pictures http://pro./ ? Corbis sells high-quality images for use in advertising, marketing, illustrating, etc. ? Search is entirely by keywords. ? Human indexers look at each new image and enter keywords. ? A thesaurus constructed from user queries is used. QBIC IBM’s QBIC (Query by Image Content) . ? The mercial system. ? Uses or has-used color pe rcentages, color layout, texture, shape, loca tion, and keywords. 2 Blobworld UC Berkeley’s Blobworld ?Images are segmented on color plus texture ? User selects a region of the query image ? System returns images with similar regions ? Works really well for tigers and zebras Ditto Ditto: See the Web ? pany ? Allows you to search for pictures from web pages Image Features / Distance Measures Image Database Query Image Distance Measure Retrieved Images Image Feature Extraction User Feature Space Images Features ? Color (histograms, gridded layout, wavelets) ?Texture (Laws, Gabor filters, local binary partition) ? Shape (first segment the image, then use statistical or structural shape similarity measures) ? Objects and their Relationships This is the most powerful, but you have to be able to recognize the objects! Color Histograms QBIC’s Histogram Similarity The QBIC color histogram distance is: d hist(