Spatial visualization for content-based image retrieval

In traditional content-based image retrieval (CBIR), the retrieved images are displayed in order of decreasing similarities from the query and can be considered as a 1-D display. In this paper, a novel optimized technique is proposed to visualize the retrieved images not only in order of their decreasing similarities but also according to their mutual similarities visualized on a 2-D screen. Principle Component Analysis (PCA) is first performed on the retrieved images to project the images from the original high dimensional feature space to 2-D screen. The result of PCA analysis is denoted as a PCA Splat. To minimize the overlap between images, a constrained nonlinear optimization approach is used. The experimental results show a more perceptually intuitive and informative visualization of the retrieval results. The proposed technique not only provides a better understanding of the query results but also aids the user in forming a new query.