Topographie metrics for image segmentation
Andras Horvath, Dániel Hillier · 2010 12th International Workshop on Cellular Nanoscale Networks and their Applications (CNNA 2010) · 2010
Algorithms designed for machine vision applications such as medical imaging, surveillance, etc., very often require some kind of comparison between images. While the brain can compare complex objects with ease, the same is usually a very difficult task for algorithm designers. Comparison between objects requires a proper definition of a metric that determines the similarity of the objects. This paper briefly investigates the problems about commonly used metrics (Hamming, Hsausdorff), and shows another method: the nonlinear wave metric, describing its advantages, and its application in practice.