Image segmentation by histogram thresholding using hierarchical cluster analysis

Authors:
Agus Zainal Arifin;Akira Asano
Affiliations:
Graduate School of Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi Hiroshima 739-8527, Japan;Division of Mathematical and Information Sciences, Faculty of Integrated Arts and Sciences, Hiroshima University, 1-7-1 Kagamiyama, Higashi Hiroshima 739-8521, Japan
Venue:
Pattern Recognition Letters
Year:
2006

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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.