MULTITHRESHOLDING IN GRAYSCALE IMAGE USING PEA FINDING APPROACH AND HIERARCHICAL CLUSTER ANALYSIS
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.
Author: Cahyono, Gigih
Prasetyo, Adrianus Yoza, Ramadhan Hani
Journal Code: jptkomputergg140014
