Dynamic image segmentation method using hierarchical clustering

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Abstract

In this paper we explore the use of the cluster analysis in segmentation problems, that is, identifying image points with an indication of the region or class they belong to. The proposed algorithm uses the well known agglomerative hierarchical cluster analysis algorithm in order to form clusters of pixels, but modified so as to cope with the high dimensionality of the problem. The results of different stages of the algorithm are saved, thus retaining a collection of segmented images ordered by degree of segmentation. This allows the user to view the whole collection and choose the one that suits him best for his particular application. © 2009 Springer-Verlag Berlin Heidelberg.

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APA

Galbiati, J., Allende, H., & Becerra, C. (2009). Dynamic image segmentation method using hierarchical clustering. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5856 LNCS, pp. 177–184). https://doi.org/10.1007/978-3-642-10268-4_21

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