Title :
Hierarchical evolving mean-shift
Author :
Surkala, Milan ; Mozdren, Karel ; Fusek, Radovan ; Sojka, Eduard
Author_Institution :
FEECS, VSB-Tech. Univ. of Ostrava, Poruba, Czech Republic
fDate :
Sept. 30 2012-Oct. 3 2012
Abstract :
Segmentation and filtration are widely discussed problems in image processing. Mean shift and its variants belong to the most popular methods in this area. In this paper, we propose a new variant of relatively new evolving mean shift that is based on the idea of minimization of dataset energy given by the sum of sizes of the mean-shift vectors. Our hierarchical EMS is focused on a significant reduction of computational time due to hierarchical evolution of the size of the kernel. We also present acceleration of precise point selection and vector recalculation, which can be applied also to original EMS.
Keywords :
filtering theory; image segmentation; computational time reduction; dataset energy minimization; hierarchical EMS; hierarchical evolving mean-shift; image filtration; image processing; image segmentation; kernel size hierarchical evolution; mean-shift vector size sum; point selection; vector recalculation; Acceleration; Bandwidth; Energy management; Equations; Image segmentation; Kernel; Vectors; evolving; hierarchy; image; mean-shift; segmentation;
Conference_Titel :
Image Processing (ICIP), 2012 19th IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4673-2534-9
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2012.6467179
