Image retrieval: Benchmarking visual information indexing and retrieval systems
β Scribed by Abebe Rorissa
- Publisher
- American Society for Information Science and Technology
- Year
- 2008
- Tongue
- English
- Weight
- 390 KB
- Volume
- 33
- Category
- Article
- ISSN
- 0095-4403
No coin nor oath required. For personal study only.
β¦ Synopsis
hat do cameras, Hollywood, flick, YouTube Broadcast W Yourself, magnetic resonance imaging (MRI) and computed tomography (CT) scans have in common? Among other things, they are tools or services or places for the creation, production, organization, management and sharing of images and/or videos. Information sources are becoming increasingly multimedia in nature. For the sake of brevity and delimiting the scope, this article will focus only on visual information, more specifically indexing and retrieval of image and video. As you may be aware from current technology events, news and controversies, Flickr (www.flickr.com) is a popular digital photo storage and sharing website and service, while YouTube (www.youtube.com), acquired recently (November 13,2006) by Google, Inc, is perhaps the most popular free video sharing website.
π SIMILAR VOLUMES
Multimedia information indexing and retrieval systems are required to manage and use ever increasing multimedia information effectively and efficiently. This paper first provides an over-view of general capabilities and architecture of multimedia information indexing and retrieval systems, and then
Our starting point is gradient indexing, the characterization of texture by a feature vector that comprises a histogram derived from the image gradient field. We investigate the use of gradient indexing for texture recognition and image retrieval. We find that gradient indexing is a robust measure w