Image segmentation by histogram thresholding using hierarchical cluster analysis

Agus Zainal Arifin; Akira Asano

doi:10.1016/j.patrec.2006.02.022

Image segmentation by histogram thresholding using hierarchical cluster analysis

Agus Zainal Arifin^*, Akira Asano

^*Corresponding author for this work

Hiroshima University

Research output: Contribution to journal › Article › peer-review

186 Citations (Scopus)

Abstract

This paper proposes a new method of image thresholding by using cluster organization from the histogram of an image. A new similarity measure proposed is based on inter-class variance of the clusters to be merged and the intra-class variance of the new merged cluster. Experiments on practical images illustrate the effectiveness of the new method.

Original language	English
Pages (from-to)	1515-1521
Number of pages	7
Journal	Pattern Recognition Letters
Volume	27
Issue number	13
DOIs	https://doi.org/10.1016/j.patrec.2006.02.022
Publication status	Published - 1 Oct 2006
Externally published	Yes

Keywords

Clustering
Image thresholding
Inter-class variance
Intra-class variance

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10.1016/j.patrec.2006.02.022

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title = "Image segmentation by histogram thresholding using hierarchical cluster analysis",

abstract = "This paper proposes a new method of image thresholding by using cluster organization from the histogram of an image. A new similarity measure proposed is based on inter-class variance of the clusters to be merged and the intra-class variance of the new merged cluster. Experiments on practical images illustrate the effectiveness of the new method.",

keywords = "Clustering, Image thresholding, Inter-class variance, Intra-class variance",

author = "Arifin, {Agus Zainal} and Akira Asano",

year = "2006",

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doi = "10.1016/j.patrec.2006.02.022",

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AU - Arifin, Agus Zainal

AU - Asano, Akira

PY - 2006/10/1

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N2 - This paper proposes a new method of image thresholding by using cluster organization from the histogram of an image. A new similarity measure proposed is based on inter-class variance of the clusters to be merged and the intra-class variance of the new merged cluster. Experiments on practical images illustrate the effectiveness of the new method.

AB - This paper proposes a new method of image thresholding by using cluster organization from the histogram of an image. A new similarity measure proposed is based on inter-class variance of the clusters to be merged and the intra-class variance of the new merged cluster. Experiments on practical images illustrate the effectiveness of the new method.

KW - Clustering

KW - Image thresholding

KW - Inter-class variance

KW - Intra-class variance

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U2 - 10.1016/j.patrec.2006.02.022

DO - 10.1016/j.patrec.2006.02.022

M3 - Article

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VL - 27

SP - 1515

EP - 1521

JO - Pattern Recognition Letters

JF - Pattern Recognition Letters

IS - 13

ER -

Image segmentation by histogram thresholding using hierarchical cluster analysis

Abstract

Keywords

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