## Abstract

Tree-based hierarchical image representations are commonly used in connected morphological image filtering, segmentation and multi-scale analysis. In the case of component trees, filtering is generally based on thresholding single attributes computed for all the nodes in the tree. Alternatively, so-called shapings are used, which rely on building a component tree of a component tree to filter the image. Neither method is practical when using vector attributes. In this case, more complicated machine learning methods are required, including clustering methods.

In this paper I present a simple, fast hierarchical clustering algorithm based on cuts of α-trees to simplify and filter component trees.

In this paper I present a simple, fast hierarchical clustering algorithm based on cuts of α-trees to simplify and filter component trees.

Original language | English |
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Title of host publication | Discrete Geometry and Mathematical Morphology 2022 |

Editors | É. Baudrier, B Naegel, A. Krähenbühl, M. Tajine |

Place of Publication | Cham |

Publisher | Springer International Publishing AG |

Pages | 236-247 |

Number of pages | 12 |

ISBN (Electronic) | 978-3-031-19897-7 |

ISBN (Print) | 978-3-031-19896-0 |

DOIs | |

Publication status | Published - 20-Oct-2022 |

Event | Discrete Geometry and Mathematical Morphology 2022 - Starsbourg, France Duration: 24-Oct-2022 → 27-Oct-2022 https://dgmm2022.sciencesconf.org/ |

### Publication series

Name | Lecture Notes in Computer Science |
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Publisher | Springer |

Volume | 13493 |

ISSN (Print) | 0302-9743 |

ISSN (Electronic) | 1611-3349 |

### Conference

Conference | Discrete Geometry and Mathematical Morphology 2022 |
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Abbreviated title | DGMM 2022 |

Country/Territory | France |

City | Starsbourg |

Period | 24/10/2022 → 27/10/2022 |

Internet address |