DocumentCode
3412187
Title
Feature space region growing
Author
Revol-Muller, C. ; Grenier, T. ; Ting Li ; Benoit-Cattin, H.
Author_Institution
CREATIS, Univ. de Lyon 1, Lyon, France
fYear
2012
fDate
Sept. 30 2012-Oct. 3 2012
Firstpage
2585
Lastpage
2588
Abstract
We propose a framework for the segmentation by region growing approach leveraging on feature space. It has the advantages to deal with multidimensional data and easily specify locally adaptive segmentation. It relies upon the definition of a robust neighborhood which drives the region growing. We propose two applications to illustrate this framework: a segmentation of physical parameters maps of MRI by using n-dimensional region growing and a segmentation of highly noisy image by using adaptive region growing.
Keywords
feature extraction; image segmentation; magnetic resonance imaging; MRI; adaptive region growing approach segmentation; feature space region; multidimensional data; n-dimensional region; noisy image segmentation; physical parameters maps segmentation; robust neighborhood; Estimation; Image segmentation; Indexes; Kernel; Magnetic resonance imaging; Noise measurement; Robustness; Feature space; Region growing; Segmentation;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing (ICIP), 2012 19th IEEE International Conference on
Conference_Location
Orlando, FL
ISSN
1522-4880
Print_ISBN
978-1-4673-2534-9
Electronic_ISBN
1522-4880
Type
conf
DOI
10.1109/ICIP.2012.6467427
Filename
6467427
Link To Document