2D Euclidean distance transform algorithms 论文

2008ACM Computing Surveys引用 499
Medical Image Segmentation TechniquesImage and Object Detection TechniquesRobotics and Sensor-Based Localization

摘要

The distance transform (DT) is a general operator forming the basis of many methods in computer vision and geometry, with great potential for practical applications. However, all the optimal algorithms for the computation of the exact Euclidean DT (EDT) were proposed only since the 1990s. In this work, state-of-the-art sequential 2D EDT algorithms are reviewed and compared, in an effort to reach more solid conclusions regarding their differences in speed and their exactness. Six of the best algorithms were fully implemented and compared in practice.