Abstract
We present a parallel algorithm for the Euclidean distance transformation (EDT). It is a “divide-and-conquer” algorithm based on a fast sequential algorithm for the signed EDT (SEDT). The combining step that follows the local partial calculation of the SEDT can be done efficiently after reformulating the SEDT problem as the partial calculation of a Voronoi diagram. This leads to an algorithm with two local calculation steps with a computational complexity proportional to the number of pixels of the subregions and a global calculation step with complexity proportional to the image perimeter. This article contains a description of the algorithm, a complexity analysis, a discussion on load imbalance, and timings obtained on an iPSC/2.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
