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
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