Feature Selection for Automatic Image Annotation

Automatic image annotation empowers the user to search an image database using keywords, which is often a more practical option than a query-by-example approach. In this work, we present a novel image annotation scheme which is fast and effective and scales well to a large number of keywords. We first provide a feature weighting scheme suitable for image annotation, and then an annotation model based on the one-class support vector machine. We show that the system works well even with a small number of visual features. We perform experiments using the Corel Image Collection and compare the results with a wellestablished image annotation system.