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Evaluation of shape descriptors for shape-based image retrieval

Evaluation of shape descriptors for shape-based image retrieval

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This article presents a comparative study between scale, rotation and translation invariant descriptors for shape representation and retrieval. Since shape is one of the most widely used image feature exploited in content-based image retrieval systems, the authors studied for each descriptor, the number of coefficients needed for indexing and their retrieval performance. Specifically, the authors studied Fourier, curvature scale space, angular radial transform (ART) and image moment descriptors for shape representation. The four shape descriptors are evaluated against each other using the standard methodology and the two most appropriate and available databases. The results showed that moment descriptors present the best performance in terms of shape representation quality while ART presents the lowest descriptor size.

References

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      • Latecki, L., Lakamper, R., Eckhardt, U.: `Shape descriptors for non-rigid shapes with a single closed contour', IEEE Conf. on Computer Vision and Pattern Recognition, 2000, 1.
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      • F. Mokhtarian , M. Bober . (2003) Curvature scale space representation: theory, applications, and MPEG-7 standardization.
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      • Latecki, L., Lakamper, R., Eckhardt, T.: `Shape descriptors for non-rigid shapes with a single closed contour', Proc. IEEE Conf. on Computer Vision and Pattern Recognition, 2000, 1.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-ipr.2009.0246
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