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Robust texture features for still-image retrieval

Howarth, P. and Rüger, S. (2005). Robust texture features for still-image retrieval. IEE Proceedings Vision, Image & Signal Processing, 152(6) pp. 868–874.

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A detailed evaluation of the use of texture features in a query-by-example approach to image retrieval is presented. Three radically different texture feature types motivated by i) statistical, ii) psychological and iii) signal processing points of view are used. The features were evaluated and tuned on retrieval tasks from the Corel collection and then evaluated and tested on the TRECVID 2003 and ImageCLEF 2004 collections. For the latter two the effects of combining texture features with a colour feature were studied. Texture features that perform particularly well are identified, demonstrating that they provide robust performance across a range of datasets.

Item Type: Journal Item
ISSN: 1350-245X
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 11947
Depositing User: Users 8580 not found.
Date Deposited: 08 Oct 2008 13:05
Last Modified: 02 May 2018 12:53
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