Journal of Systems and Software - Special issue: Automated component-based software engineering
Exploring the relationship between feature and perceptual visual spaces
Journal of the American Society for Information Science and Technology
Interactive access to large image collections using similarity-based visualization
Journal of Visual Languages and Computing
An Interactive Image Feature Visualization System for Supporting CBIR Study
ICIAR '09 Proceedings of the 6th International Conference on Image Analysis and Recognition
Proceedings of the International Conference on Advanced Visual Interfaces
Index support for content-based multimedia exploration
Proceedings of the international conference on Multimedia
A kernel-based framework for image collection exploration
Journal of Visual Languages and Computing
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The proliferation of content-based image retrieval techniques has highlighted the need to understand the relationship between image clustering based on low-level image features and image clustering made by human users. In conventional image retrieval systems, a range of features such as color, texture, and shape typically characterizes images. However, little is known to what extent these low-level 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 such features. Salient structures of images are visualized according to features extracted from color, texture, and shape orientation. Implications for visualizing and constructing hypermedia systems are discussed.