Researchers at Penn State University in the College of Information Sciences & Technology have developed software that can automatically recognize image content and properly "tag" it in plain English.  This would present a significant improvement to image search engines that rely on manually entered tags to describe image content.  The article linked below uses an example of a photo of a polo match being tagged by the system with words such as "sport", "people", "horse", and "polo."

The system is called the Automatic Linguistic Indexing of Pictures Real-Time (ALIPR) and it currently has a vocabulary of 332 words to describe what it detects in an image.  The project is headed by associate professors James Wang and Jia Li.

The system is "trained" by inputting vast numbers of pictures, and then telling the program which automatically selected tags are correct.  The idea is that as more images are uploaded and more tags identified, the more accurate it becomes.  Currently, more than half the time, the first tag the computer selects out of 15 is correct.  The analysis takes about 1.4 seconds per image and has a 98% success rate in identifying at least one correct tag.

If you're interested in trying the system out for yourself, they've opened up the project on Dr. Wang's website so you can help improve the system by uploading your own images and selecting the correct tags.  http://www.alipr.com/

For further information on Dr. Wang's image analysis research, check here: http://wang.ist.psu.edu/IMAGE/

This technology is very promising for companies like Google who are attempting to improve their image processing and search capabilities.