Image retrieval

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An image retrieval system is a computer system for browsing, searching and retrieving images from a large database of digital images. Most traditional and common methods of image retrieval utilize some method of adding metadata such as captioning, keywords, or descriptions to the images so that retrieval can be performed over the annotation words. Manual image annotation is time-consuming, laborious and expensive; to address this, there has been a large amount of research done on automatic image annotation. Additionally, the increase in social web applications and the semantic web have inspired the development of several web-based image annotation tools.

The first microcomputer-based image database retrieval system was developed at MIT, in the 1980s, by Banireddy Prasad, Amar Gupta, Hoo-min Toong, and Stuart Madnick.^[1]

Another method of image retrieval is content-based image retrieval (CBIR), which aims at avoiding the use of textual descriptions and instead retrieves images based on their visual similarity to a user-supplied query image or user-specified image features.

Contents 1 Evaluations 2 See also 3 References 4 External links

[edit] Evaluations

There are evaluation workshops for image retrieval systems aiming to investigate and improve the performance of such systems.

• ImageCLEF - a continuing track of the Cross Language Evaluation Forum that evaluates systems using both textual and pure-image retrieval methods.
• Content-based Access of Image and Video Libraries - a series of IEEE workshops from 1998 to 2001.

[edit] See also

• Computer vision
• Digital asset management
• Digital image editing
• Information retrieval
• Image processing

[edit] References

1. ^ Prasad, B E; A Gupta, H-M Toong, S.E. Madnick (February 1987). "A microcomputer-based image database management system". IEEE Transactions on Industrial Electronics IE-34 (1): 83-8. doi:10.1109/TIE.1987.350929. 

[edit] External links

• alipr.com Automatic image tagging and visual image search. Developed with Stanford and Penn State technologies.

• CIRES Image retrieval system developed by the University of Texas at Austin.

• FIRE Image retrieval system developed by the RWTH Aachen University, Aachen, Germany.

• GIFT GNU Image Finding Tool, originally developed at the University of Geneva, Switzerland.

• IEEE CBAIVL Proceedings

• ImageCLEF A benchmark to compare the performance of image retrieval systems.

• imgSeek Open-source desktop photo collection manager and viewer with content-based search and many other features.

• img(Anaktisi) This Web-Solution implements a new family of CBIR descriptors. These descriptors combine in one histogram color and texture information and are suitable for accurately retrieving images.