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.
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