An integrated approach to computational vision - The edge strength function and the nested symmetries

Date

1999-01-01

Author

Tarı, Zehra Sibel

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A new development in local symmetry extraction and its connections to segmentation functionals and the fronts propagating with curvature-dependent speed are examined. The basic tool is a new distance function that attains its maximum value at the shape boundary and decays rapidly away from there. It is shown that the Hessian of the distance function captures perceptual information that can be extracted easily, efficiently, and robustly in the form of nested local shape symmetries at multiple scales. The most important property of the distance function is that it can be computed from unprocessed images; thus the segmentation loci of an image can be represented without the knowledge of the segmentation loci itself. The formulation is also valid for shapes in any dimension.

Subject Keywords

Shape, Images

URI

https://hdl.handle.net/11511/57983

Journal

ADVANCES IN IMAGING AND ELECTRON PHYSICS, VOL 111

DOI

https://doi.org/10.1016/s1076-5670(08)70220-9

Collections

Department of Computer Engineering, Article

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Citation Formats

Z. S. Tarı, “An integrated approach to computational vision - The edge strength function and the nested symmetries,” ADVANCES IN IMAGING AND ELECTRON PHYSICS, VOL 111, pp. 327–366, 1999, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/57983.