Statistically Valid Graph Representations of Scale-Space Geometry

Authors:
Tomoya Sakai;Atsushi Imiya
Affiliations:
Institute of Media and Information Technology, Chiba University, Japan;Institute of Media and Information Technology, Chiba University, Japan
Venue:
ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
Year:
2008

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Abstract

This paper presents a statistical scale-selection criterion for graph representations derived from differential geometric features of a greyscale image in a Gaussian scale space. The image gradient in scale space derives hierarchical and topological relationships among the bright and dark components in the image. These relationships can be represented as a tree and a skeleton-like graph, respectively. Since the image at small scales contains invalid geometric features due to noise and numerical errors, a validation scheme is required for the detected features. The presented scale-selection criterion allows us to identify the valid features used for the graph representations with statistical confidence.