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2001
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Support vector machine learning for image retrieval

9 years 10 months ago
Support vector machine learning for image retrieval
In this paper, a novel method of relevance feedback is presented based on Support Vector Machine learning in the content-based image retrieval system. A SVM classifier can be learned from training data of relevance images and irrelevance images marked by users. Using the classifier, the system can retrieve more images relevant to the query in the database efficiently. Experiments were carried out on a large-size database of 9918 images. It shows that the interactive learning and retrieval process can find correct images increasingly. It also shows the generalization ability of SVM under the condition of limited training samples.
Lei Zhang, Fuzong Lin, Bo Zhang
Added 25 Oct 2009
Updated 27 Oct 2009
Type Conference
Year 2001
Where ICIP
Authors Lei Zhang, Fuzong Lin, Bo Zhang
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