Simultaneous fuzzy segmentation of multiple objects

Fuzzy segmentation is a technique that assigns to each element in an image (which may have been corrupted by noise and/or shading) a grade of membership in an object (which is believed to be contained in the image). In an earlier work, the first two authors extended this concept by presenting and il...

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Bibliographic Details
Published inDiscrete Applied Mathematics Vol. 151; no. 1; pp. 55 - 77
Main Authors Carvalho, Bruno M., Herman, Gabor T., Kong, T. Yung
Format Journal Article Conference Proceeding
LanguageEnglish
Published Lausanne Elsevier B.V 01.10.2005
Amsterdam Elsevier
New York, NY
Subjects
Algorithmics. Computability. Computer arithmetics
Applied sciences
Artificial intelligence
Biological and medical sciences
Combinatorics
Combinatorics. Ordered structures
Computer science; control theory; systems
Exact sciences and technology
Fundamental and applied biological sciences. Psychology
Fuzzy graphs
Fuzzy segmentation
General aspects
Graph theory
Greedy algorithms
Mathematics
Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)
Pattern recognition. Digital image processing. Computational geometry
Sciences and techniques of general use
Theoretical computing
Greedy algorithms
Fuzzy graphs
Fuzzy segmentation
Computer theory
Imaging
Greedy algorithm
Combinatorics
Biomedical imaging
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Summary:Fuzzy segmentation is a technique that assigns to each element in an image (which may have been corrupted by noise and/or shading) a grade of membership in an object (which is believed to be contained in the image). In an earlier work, the first two authors extended this concept by presenting and illustrating an algorithm which simultaneously assigns to each element in an image a grade of membership in each one of a number of objects (which are believed to be contained in the image). In this paper, we prove the existence of such a fuzzy segmentation that is uniquely specified by a desirable mathematical property, show further examples of its use in medical imaging, and illustrate that on several biomedical examples a new implementation of the algorithm that produces the segmentation is approximately seven times faster than the previously used implementation. We also compare our method with two recently published related methods.
ISSN:0166-218X
1872-6771
DOI:10.1016/j.dam.2005.02.031