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IV
2000
IEEE

Content-Based Image Visualization

10 years 4 months ago
Content-Based Image Visualization
The proliferation of content-based image retrieval techniques has highlighted the need to understand the relationship between image clustering based on low-Ievel imagefeatures and image clustering made by human users. In conventional image retrieval systems, images are typically characterized by a range offeatures such as color, texture, and shape. However, little is known to what extent these low-Ievel features can be effectively combined with information visualization techniques such that users may explore images in a digital library according to visual similarities. In this article, we compared and analyzed a number of Pathfinder networks of images generated based on suchfeatures. Salient structures of images are visualized according to features extracted .from color, texture, and shape orientation. Implications for visualizing and constructing hypermedia systemsare discussed.
Chaomei Chen, George Gagaudakis, Paul L. Rosin
Added 31 Jul 2010
Updated 31 Jul 2010
Type Conference
Year 2000
Where IV
Authors Chaomei Chen, George Gagaudakis, Paul L. Rosin
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