DocumentCode :
1207572
Title :
Adaptive image region-growing
Author :
Chang, Yian-Leng ; Li, Xiaobo
Author_Institution :
Dept. of Comput. Sci., Alberta Univ., Edmonton, Alta., Canada
Volume :
3
Issue :
6
fYear :
1994
fDate :
11/1/1994 12:00:00 AM
Firstpage :
868
Lastpage :
872
Abstract :
Proposes a simple, yet general and powerful, region-growing framework for image segmentation. The region-growing process is guided by regional feature analysis; no parameter tuning or a priori knowledge about the image is required. To decide if two regions should be merged, instead of comparing the difference of region feature means with a predefined threshold, the authors adaptively assess region homogeneity from region feature distributions. This results in an algorithm that is robust with respect to various image characteristics. The merge criterion also minimizes the number of merge rejections and results in a fast region-growing process that is amenable to parallelization
Keywords :
adaptive signal processing; image segmentation; minimisation; adaptive image region-growing; image characteristics; merge criterion; minimization; parallelization; region feature distributions; region homogeneity; region-growing framework; regional feature analysis; Councils; Histograms; Image analysis; Image segmentation; Robustness; Testing;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/83.336259
Filename :
336259
Link To Document :
بازگشت