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A New Contiguity-Constrained Agglomerative Hierarchical Clustering Algorithm for Image Segmentation

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Current Topics in Artificial Intelligence (CAEPIA 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5988))

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Abstract

This paper introduces a new constrained hierarchical agglomerative algorithm with an aggregation index which uses neighbouring relations present in the data. Experiments show the behaviour of the proposed contiguity-constrained agglomerative hierarchical algorithm in the case of medical image segmentation.

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Author information

Authors and Affiliations

  1. Faculty of Informatics, University of Cienfuegos, Cuatro Caminos, Cienfuegos, Cuba

    Eduardo R. Concepción Morales

  2. Department of Computer Science and Artificial Intelligence, University of the Basque Country/EHU, Campus Guipuzcoa, Donostia-San Sebastian, Spain

    Yosu Yurramendi Mendizabal

Authors
  1. Eduardo R. Concepción Morales
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  2. Yosu Yurramendi Mendizabal
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Editor information

Editors and Affiliations

  1. IIIA - CSIC, Campus UAB s/n, 08193, Bellaterra, Spain

    Pedro Meseguer

  2. Dpto. Lenguajes y Ciencias de la Computación, Universidad de Málaga, Campus de Teatinos, 29071, Málaga, Spain

    Lawrence Mandow

  3. Dpto. Lenguajes y Sistemas Informáticos, ETS Ingeniería Informática, University of Seville, Av. Reina Mercedes S/N, 41012, Sevilla, Spain

    Rafael M. Gasca

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Morales, E.R.C., Yurramendi Mendizabal, Y. (2010). A New Contiguity-Constrained Agglomerative Hierarchical Clustering Algorithm for Image Segmentation. In: Meseguer, P., Mandow, L., Gasca, R.M. (eds) Current Topics in Artificial Intelligence. CAEPIA 2009. Lecture Notes in Computer Science(), vol 5988. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14264-2_27

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  • DOI: https://doi.org/10.1007/978-3-642-14264-2_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-14263-5

  • Online ISBN: 978-3-642-14264-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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