A visual search engine enables users to search and find visual information contained in images, graphics, videos, etc. There are two approaches to retrieving visual information: text-based and content-based. Text-based search engines rely on manual annotation of the images and videos. Content-based or Visual Search engines rely on visual properties such as color, texture, shape, etc. These properties are automatically extracted from the images and videos based on image processing and pattern recognition techniques.
Using a text-based search engine to search the Internet or a database often produces a large number of inaccurate or irrelevant results. For example, a recent search on Altavista.com for "Angels" turned up links to Web sites for Charlie's Angels, the Blue Angels, Angel perfume, the Guardian Angels, the neurogenetic disorder Angelman's syndrome, Vanessa Angel, a schedule for the Anaheim Angels baseball team Angel fish, and references to the biblical Angel.
Text-based search engines or Digital Asset Management (DAM) software offer image searches that comb the data based on the text file names attached to images. If the file name for an image is not representative of that image, or if a user does not know what words to input, a text-based search is inadequate and can be frustrating.
In contrast to text-based searching, a visual search looks inside the actual image and uses mathematical algorithms that analyze color, shape, and texture to help produce more accurate results. Users can select a query image, such as the image of a sunset, and then "Zero In" their search to find similar pictures, either by color, shape, texture or object.