Fast watershed-based dilation

• Autorzy: Smołka J.
• Języki publikacji: EN

Abstrakty

EN

A watershed-based region growing image segmentation algorithm requires a fast watershed-based dilation implementation for effective operation. This paper presents a new way for watershed image representation and uses this representation for effective implementation of dilation. Methods for improving the algorithm speed are discussed. Presented solutions may also be used for solving other problems where fast set summation is required.

Słowa kluczowe

EN

image processing; dilation; watershed transformation

• Wydawca: Lublin University of Technology ; Polish Society of Ecological Engineering (PTIE), Branch of PTIE in Lublin
• Czasopismo: Advances in Science and Technology. Research Journal
• Rocznik: 2014
• Tom: Vol. 8, nr 23
• Strony: 41--44
• Opis fizyczny: Bibliogr. 7 poz., tab.

Twórcy

autor

Smołka J.

• Section of Computers Science, Department of Technical Sciences, Pope John Paul II State School of Higher Education in Biała Podlaska, Sidorska 95/97, 21-500 Biała Podlaska, Poland

Bibliografia

• 1. Smołka J., Watershed Based Region Growing Algorithm. Annales Informatica UMCS AI 3, 2005, 169–178.
• 2. Beucher S., Lantuejoul C., Use of watersheds in contour detection. International Workshop on Image Processing: Real-time Edge and Motion Detection/Estimation, 1979.
• 3. Beucher S., The watershed transformation applied to image segmentation. Scanning Microscopy International, 6, 1992, 299–314.
• 4. Ibanez L., Schroeder W., Ng L., Cates J., The ITK Software Guide. Kitware Inc., 2003.
• 5. Seul M., O’Gorman L., Sammon M.J., Practical Algorithms for Image Analysis: Description. Examples, and Code, Cambridge Univerisity Press 2000.
• 6. Gonzalez R.C., Woods R.E., Digital Image Processing. Addison-Wesley Publishing Company 1993.
• 7. Standard Template Library Programmer’s Guide http://www.sgi.com/tech/stl/