Abstract
Measuring image similarity is important for a number of image processing applications. The goal of research in objective image similarity assessment is to develop quantitative measures that can automatically predict perceived image similarity. In this paper, we propose a new objective approach of measuring image similarity based on shape context. We take the geometric structures of objects into account during measuring the image similarity by virtue of shape context which is a robust and compact, yet highly discriminative descriptor. Firstly we find visual salient regions of images by virtue of a regional contrast based saliency extraction algorithm and employ shape context to describe the shape of visual salient region. Then we detect shape deformations of visual salient regions between two images through estimating shape context distances, and accordingly compute the image similarity values. Real data have been used to test the proposed approach and very good results have been achieved, validating it.
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