Application of discriminant-EM in image retrieval by relevance feedback
Document Type
Conference Proceeding
Publication Date
12-1-2004
Abstract
In this paper, we introduce a new method for retrieving images in an image database. In previously proposed Relevance Feedback methods, the user is asked to label the image examples as positive (relevant) or negative (irrelevant) images. In our model, the user can label the example images with a score between zero and one. We implemented an Expectation Maximization (EM) algorithm to be able to use unlabeled data as well as labeled data for clustering images. Also, we use discriminant analysis to give higher weights to features that are more important in discriminating relevant from irrelevant images.
Publication Source (Journal or Book title)
IIE Annual Conference and Exhibition 2004
First Page
2223
Last Page
2228
Recommended Citation
Shah-Hosseini, A., & Knapp, G. (2004). Application of discriminant-EM in image retrieval by relevance feedback. IIE Annual Conference and Exhibition 2004, 2223-2228. Retrieved from https://repository.lsu.edu/mechanical_engineering_pubs/1497