Parallel algorithms for the distance transformation
The distance transformation (DT) is a basic operation in image analysis where it is used for object recognition.
We present several approaches for the parallel calculation of the distance transform. They are of the kind “divide- and-conquer” and are similar in this respect to the parallel algorithm we have developed for component labelling. Concrete algorithms and their performance will be discussed for the city block (CB) distance and the Chamfer 3–4 distance that are approximations for the Euclidean Distance.
Keywordsdistance transformation MIMD machines divide and conquer image analysis
Unable to display preview. Download preview PDF.
- 1.G. Borgefors. Distance transformations in arbitrary dimensions. Computer Vision, Graphics and Image Processing, 27(3):321–345, 1984.Google Scholar
- 2.G. Borgefors. Distance transformations in digital images. Computer Vision, Graphics and Image Processing, 34(3):344–371, 1986.Google Scholar
- 3.G. Borgefors, T. Hartmann, and S. L. Tanimoto. Parallel distance transforms on pyramid machines: Therory and implementation. Signal processing, 21:61–86, 1990.Google Scholar
- 4.H. Embrechts and D. Roose. Parallel algorithms for the distance transformation. Technical Report TW151, Katholieke Universiteit Leuven, 1991.Google Scholar
- 5.H. Embrechts, D. Roose, and P. Wambacq. Component labelling on an MIMD multiprocessor. Computer Vision, Graphics and Image Processing: Image Understanding, to appear.Google Scholar
- 6.S. Miguet. Distance transform on a ring of processors. In M. Cosnard and C. Giraud, editors, Working Conference on Decentralized Systems, pages 285–296. North-Holland, 1990.Google Scholar