MULTITHRESHOLDING IN GRAYSCALE IMAGE USING PEA FINDING APPROACH AND HIERARCHICAL CLUSTER ANALYSIS

Authors

  • Cahyono Cahyono
  • Gigih Prasetyo
  • Adrianus Yoza
  • Ramadhan Hani

DOI:

https://doi.org/10.21609/jiki.v7i2.261

Keywords:

segmentation, multithresholding, peak finding, merging, cluster analysis

Abstract

Abstract Image segmentation is typically used to distinguish objects that exist in an image. However, it remains difficult to accommodate favourable thresholding in multimodal image histogram problem with specifically desired number of thresholds. This research proposes a novel approach to find thresholds in multimodal grayscale image histogram. This method consists of histogram smoothing, identification of peak(s) and valley(s), and merging process using hierarchical cluster analysis. Using five images that consisted of grayscale and converted-to-grayscale images. This method yields maximum value of accuracy, precision, and recall of 99.93%, 99.75%, and 99.75% respectively. These results are better than the similar peak finding method in multimodal grayscale image segmentation.

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Published

2014-08-21

How to Cite

Cahyono, C., Prasetyo, G., Yoza, A., & Hani, R. (2014). MULTITHRESHOLDING IN GRAYSCALE IMAGE USING PEA FINDING APPROACH AND HIERARCHICAL CLUSTER ANALYSIS. Jurnal Ilmu Komputer Dan Informasi, 7(2), 83–89. https://doi.org/10.21609/jiki.v7i2.261

Issue

Vol. 7 No. 2 (2014): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information)

Section

Articles

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