Abstract
Retrieval efficiency and accuracy are two important issues in designing a content-based database retrieval system. We propose a new image database retrieval method based on shape information. This system achieves both the desired efficiency and accuracy using a two-stage hierarchy: in the first stage, simple and easily computable statistical shape features are used to quickly browse through the database to generate a moderate number of plausible retrievals; in the second stage, the outputs from the first stage are screened using a deformable template matching process to discard spurious matches. We have tested the algorithm using hand drawn queries on a trademark database containing 1,100 images. Each retrieval takes a reasonable amount of computation time. The top most retrieved image from the system agrees with that obtained by human subjects, but there are significant differences between the top 10 retrieved images by our system and that provided by human subjects. This demonstrates the need for developing shape features that are better able to capture human perceptual similarity of shapes.
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