Image Transformation With Lung Image Thresholding
and Segmentation Method

Image Transformation With Lung Image Thresholding
and Segmentation Method

transformation; image; threshold; segmentation; lung

Image transformation is important to obtain and find certain information about an image that was not previously known, such
as pixels, geometry, size, and color. Following this, this research aims to analyze image transformation in producing better
values using threshold and segmentation methods. The segmentation process is carried out based on two color models, namely
hue saturation value (HSV) and red green blue (RGB). The image data used in this study was the x-ray image of the lungs from
www.fk.unair.ac.id. which is processed using the Matlab 2021a application to help the analysis process. on the results of the
image segmentation analysis carried out in this case, the greater the HSV and RGB threshold values used in the image data,
the better and clearer the segmentation of the detected image results. In other words, the size of the thresholding value
generated greatly affects the quality, brightness, size, and color of the resulting image. The best lung X-ray image segmentation
results were obtained when using the threshold values HSV = 0.9 and RGB = 9

Sahat Sonang S1
, Y.Yuhandri2
, Adil Setiawan3

Politeknik Bisnis Indonesia

26-03-2023

Fajar bagus W

PDF

Indonesia

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