Automatic Lingustic Indexing of Pictures


Description
Image archives on the Internet are growing at a phenomenal rate. With digital cameras becoming increasingly affordable and the widespread use of home computers possessing hundreds of gigabytes of storage, individuals nowadays can easily build sizable personal digital photo collections. Photo sharing through the Internet has become a common practice. According to a report released in June 2005, an Internet photo-sharing startup, flickr.com, has almost one million registered users and hosts 19.5 million photos, with a growth of about 30 percent per month. More specialized online photo-sharing communities, such as photo.net and airliners.net, also have databases in the order of millions of images entirely contributed by the users.

The Problem
Image search provided by major search engines such as Google, MSN, and Yahoo! relies on textual descriptions of images found on the Web pages containing the images and the file names of the images. These search engines do not analyze the pixel content of images and hence cannot be used to search unannotated image collections. Fully computerized or computer-assisted annotation of images by words is a crucial technology to ensure the “visibility” of images on the Internet, due to the complex and fragmented nature of the networked communities.

The Solution
SIMPLIcity (Semanticssensitive Integrated Matching for Picture LIbraries), an image retrieval system, which uses semantics classification methods, a wavelet-based approach for feature extraction, and integrated region matching based upon image segmentation.

Insights
• Indexing images by analyzing their pixel content.
• This method uses an objective naming conventions for the images found in a library.
• More reliable textual description rather that just indexing images by their file names.

Best Practice
Here is the result of the system search, utilizing SIMPLIcity, responding to the keyword: Advertising. After reviewing the results, you can narrow down your search by the keywords provided on the top of the screen.

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Reference: ALIPR