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Incorporate Discriminant Analysis with EM Algorithm in Image Retrieval

8 years 11 months ago
Incorporate Discriminant Analysis with EM Algorithm in Image Retrieval
One of the difficulties of Content-Based Image Retrieval (CBIR) is the gap between high-level concepts and low-level image features, e.g., color and texture. Relevance feedback was proposed [1] to take into account of the above characteristics in CBIR. Although relevance feedback incrementally supplies more information for fine retrieval, two challenges exist: (1) the labeled images from the relevance feedback are still very limited compared to the large unlabeled images in the image database. (2) relevance feedback does not offer a specific technique to automatically weight the low-level feature. In this paper, image retrieval is formulated as a transductive learning problem by combining unlabeled images in supervised learning to achieve better classification. Experimental results show that the proposed approach has a satisfactory performance for image retrieval applications.
Qi Tian, Ying Wu, Thomas S. Huang
Added 31 Jul 2010
Updated 31 Jul 2010
Type Conference
Year 2000
Where ICMCS
Authors Qi Tian, Ying Wu, Thomas S. Huang
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