article · 2004

On Hausdorff Distance Measures

Cited by 29Abstract and details only

Abstract

A number of Hausdorff-based algorithms have been proposed for finding objects in images. We evaluate different measures and argue that the Hausdorff Average distance measure outperforms other variants for model detection. This method has improved robustness properties with respect to noise. We discuss the algorithms with respect to typical classes of noise, and we illustrate their relative performances through an example edge-based matching task. We show that this method produces a maximum a posteriori estimate. Furthermore, we argue for improved computational efficiency by tree-like subdivisions of the model and transformation spaces.

Cite this paper

APA 7

Shapiro, & Blaschko, M. B. (2004). On Hausdorff Distance Measures.

MLA 9

Shapiro, , and Matthew B. Blaschko. “On Hausdorff Distance Measures.” 2004.

Chicago

Shapiro, and Matthew B. Blaschko. 2004. “On Hausdorff Distance Measures.”

Harvard

Shapiro and Blaschko, M.B. (2004) ‘On Hausdorff Distance Measures’.

BibTeX

@article{shapiro2004hausdorff,
  title = {{On Hausdorff Distance Measures}},
  author = {Shapiro and Blaschko, Matthew B.},
  year = {2004}
}

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