Tolerance-based feature transforms (TFTs) assign to each pixel in an image not only the nearest feature pixels on the boundary (origins), but all origins from the minimum distance up to a user-defined tolerance. In this paper, we compare four simple-to-implement methods for computing TFTs on binary images. Of these methods, the Fast Marching TFT and Euclidean TFT are new. The other two extend existing distance transform algorithms. We quantitatively and qualitatively compare all algorithms on speed and accuracy of both distance and origin results. Our analysis is aimed at helping practitioners in the field to choose the right method for given accuracy and performance constraints.
|Title of host publication||Advances in Computer Graphics and Computer Vision (International Conferences VISAPP and GRAPP 2006, Setúbal, Portugal, February 25-28, 2006, Revised Selected Papers)|
|Editors||J. Braz, A. Ranchordas, H. Araújo, J. Jorge|
|Publication status||Published - 2008|
|Name||Communications in Computer and Information Science|