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Jesus Zarrazola, E. de and Gómez, Daniel and Montero, Javier and Yáñez, Javier
(2010)
*A hierarchical segmentation for image processing.*
In
2010 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC).
IEEE Conference Publications
(http:/).
IEEE, pp. 1-4.
ISBN 978-1-4244-8126-2

PDF
Restringido a Repository staff only 87kB |

Official URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5586420

URL | URL Type |
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http://www.ieee.org | Organisation |

## Abstract

Segmentation algorithms are well known in the field of image processing. In this work we propose an efficient

and polynomial algorithm for image segmentation based on

fuzzy set theory. The main difference with the classical segmentation algorithms is in the output given by the segmentation process. Since the classical output for segmentation algorithms give us the homogeneous regions in the image, our proposal is to produce an hierarchical information (in a similar way as a dendrogam does in classical clustering methods) of how the groups are formed in the image, from the initial situation in which all pixels are in the same group to the final situation in

which the whole image is divided in the minimal information

units.

Item Type: | Book Section |
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Uncontrolled Keywords: | Fuzzy set theory; Image segmentation; Pattern clustering; Polynomials |

Subjects: | Sciences > Mathematics > Logic, Symbolic and mathematical |

ID Code: | 16036 |

Deposited On: | 24 Jul 2012 09:48 |

Last Modified: | 19 Feb 2019 11:29 |

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