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2008
Springer

Comparing Dissimilarity Measures for Content-Based Image Retrieval

8 years 4 months ago
Comparing Dissimilarity Measures for Content-Based Image Retrieval
Abstract. Dissimilarity measurement plays a crucial role in contentbased image retrieval, where data objects and queries are represented as vectors in high-dimensional content feature spaces. Given the large number of dissimilarity measures that exist in many fields, a crucial research question arises: Is there a dependency, if yes, what is the dependency, of a dissimilarity measure's retrieval performance, on different feature spaces? In this paper, we summarize fourteen core dissimilarity measures and classify them into three categories. A systematic performance comparison is carried out to test the effectiveness of these dissimilarity measures with six different feature spaces and some of their combinations on the Corel image collection. From our experimental results, we have drawn a number of observations and insights on dissimilarity measurement in content-based image retrieval, which will lay a foundation for developing more effective image search technologies. Key words: di...
Haiming Liu 0002, Dawei Song, Stefan M. Rüger
Added 12 Oct 2010
Updated 12 Oct 2010
Type Conference
Year 2008
Where AIRS
Authors Haiming Liu 0002, Dawei Song, Stefan M. Rüger, Rui Hu, Victoria S. Uren
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