The Customized-Queries Approach to CBIR Using EM

This paper makes two contributions. The first contribution is an approach called the "customized-queries" approach (CQA) to content-based image retrieval. The second is an algorithm called FSSEM that performs feature selection and clustering simultaneously. The customizedqueries approach first classifies a query using the features that best differentiate the major classes and then customizes the query to that class by using the features that best distinguish the images within the chosen major class. This approach is motivated by the observation that the features that are most effective in discriminating among images from different classes may not be the most effective for retrieval of visually similar images within a class. This occurs for domains in which not all pairs of images within one class have equivalent visual similarity, i.e. subclasses exists. Because we are not given subclass labels, we must simultaneously find the features that best discriminate the subclasses a...

• Type: Conference
• Year: 1999
• Where: CVPR
• Authors: Jennifer G. Dy, Carla E. Brodley, Avinash C. Kak, Chi-Ren Shyu, Lynn S. Broderick
• Keywords: Computer Vision, Content-based Image Retrieval, Content-based Retrieval, CVPR 1999, Retrieval Precision, Single Feature Vector, Traditional Approach