Open AccessDetermination of Hue Saturation Value (HSV) color feature in kidney histology image
Author(s) -
Ima Kurniastuti,
E N I Yuliati,
Firman Yudianto,
Tri Deviasari Wulan
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2157/1/012020
Subject(s) - hue , hsl and hsv , artificial intelligence , color space , computer vision , feature (linguistics) , tubule , segmentation , glomerulus , kidney , computer science , pattern recognition (psychology) , mathematics , medicine , image (mathematics) , immunology , linguistics , virus , philosophy
The kidney is organ that plays an important role in the body’s metabolism, especially the process of filtration and reabsorption of food waste. Currently the determination of kidney parts through kidney histology is still done manually by experts based on experience and knowledge. Therefore, to make it easier to determine the parts of the kidney, a histological image segmentation of the kidney was carried out. In the segmentation process, it is necessary to extract the color features of the parts of the kidney, namely the glomerulus and proximal tubule. The color features used are Hue, saturation, value (HSV) color space. The hue means the representation of color type. The saturation defines the amount of white color is mixed with hue. The value in HSV color space denotes the intensity or lightness or brightness of the color. The method consists of three steps such as pre-processing step, extraction feature HSV and statistical analysis. The result of statistical analysis showed that the hue and value features, glomerulus and proximal tubule had different ranges of values. However, the features of saturation, glomerulus and proximal tubule is overlap.