We introduce a new method for segmentation of 3D medical data based on geometric variational principles. A minimal variance criterion is coupled with a geometric edge alignment mea...
Michal Holtzman-Gazit, Dorith Goldsher, Ron Kimmel
In this paper we present a new method for self-localization on wafers using geometric hashing. The proposed technique is robust to image changes induced by process variations, as o...
Michael Lifshits, Roman Goldenberg, Ehud Rivlin, M...
Mathematical morphology was originally conceived as a set theoretic approach for the processing of binary images. Approaches that extend classical binary morphology to gray-scale ...
An important feature of many problem domains in machine learning is their geometry. For example, adjacency relationships, symmetries, and Cartesian coordinates are essential to an...
We propose using the proximity distribution of vectorquantized local feature descriptors for object and category recognition. To this end, we introduce a novel "proximity dis...