Compressing 2-d shapes using concavity trees

Authors:
O. El Badawy;M. S. Kamel
Affiliations:
Dept. of Systems Design Engineering;Dept. of Electrical and Computer Engineering., Pattern Analysis and Machine Intelligence Research Group, University of Waterloo, Waterloo, Ontario, Canada
Venue:
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
Year:
2005

Citing 5
Cited 0

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Hierarchical representation of 2-D shapes using convex polygons: A morphological approach

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Hierarchical representation of 2-D shapes using convex polygons: a contour-based approach

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Abstract

Concavity trees have been known for quite some time as structural descriptors of 2-D shape; however, they haven't been explored further until recently. This paper shows how 2-D shapes can be concisely, but reversibly, represented during concavity tree extraction. The representation can be exact, or approximate to a pre-set degree. This is equivalent to a lossless, or lossy compression of the image containing the shape. This paper details the proposed technique and reports near-lossless compression ratios that are 150% better than the JBIG standard on a test set of binary silhouette images.