DocumentCode :
1487791
Title :
Multiseeded segmentation using fuzzy connectedness
Author :
Herman, Gabor T. ; Carvalho, Bruno M.
Author_Institution :
Center for Comput. Sci. & Appl. Math., Temple Univ., Philadelphia, PA, USA
Volume :
23
Issue :
5
fYear :
2001
fDate :
5/1/2001 12:00:00 AM
Firstpage :
460
Lastpage :
474
Abstract :
Fuzzy connectedness has been effectively used to segment out an object in a badly corrupted image. We generalize the approach by providing a definition which is shown to always determine a simultaneous segmentation of multiple objects. For any set of seed points, the segmentation is uniquely determined by the definition. An algorithm for finding this segmentation is presented and its output is illustrated. The algorithm is fast as compared to other segmentation algorithms in current use. We also report on an evaluation of the accuracy and robustness of the algorithm based on experiments in which several users were repeatedly asked to identify the seed points for the algorithm in a number of images
Keywords :
feature extraction; fuzzy set theory; image segmentation; object recognition; accuracy; fuzzy connectedness; multiseeded segmentation; robustness; seed points; Clustering algorithms; Feature extraction; Fuzzy sets; Image recognition; Image segmentation; Pixel; Psychology; Robustness; Statistics;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.922705
Filename :
922705
Link To Document :
بازگشت