A Distance Measure for Perfoemance Evaluation of Shape Adaptive Transforms

Revision of a fuzzy distance measure

A Context Dependent Distance Measure for Shape Clustering

We present a new similarity measure between a single shape and a shape group as a basis for shape clustering following the paradigm of context dependent shape comparison: clusters are generated in the context of a reference shape, defined by the query shape it is compared to. Tightly coupled, the distance measure is the basis for a soft k-means like framework to achieve robust clustering. Succe...

A new measure for distance-field based shape matching

One popular method to match two shapes is to register their distance fields as images. We discuss the well-known robustness problems of this approach and identify the noncommutativity of distance transform and geometric transformations as a core issue. Building on this, we propose a simple modification of the method, deriving a new dissimilarity measure. As it involves multiple distance field c...

A New Distance Measure for Probabilistic Shape Modeling

The contour of a planar shape is essentially one-dimensional signal embedded in 2-D space; thus the orthogonal distance, which only considers 1-D (norm) deviation from suggested models, is not rich enough to characterize the description quality of arbitrary model/shape pairs. This paper suggests a generalized distance measure, called Transport Distance, for probabilistic shape modeling. B-Splin...

Shape anisotropy: tensor distance to anisotropy measure

Fractional anisotropy (FA), defined as the distance of a diffusion tensor from its closest isotropic tensor, has been extensively studied as quantitative anisotropy measure for diffusion tensor magnetic resonance images (DT-MRI). It has been used to reveal the white matter profile of brain images, as guiding feature for seeding and stopping in fiber tractography and for the diagnosis and assess...