학술논문

Image Decoloring via Optimized Predominant Component Analysis for Segmentation of Microscopic Yeast Cell Images
Document Type
Conference
Source
2019 12th International Conference on Measurement Measurement, 2019 12th International Conference on. :190-194 May, 2019
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Engineered Materials, Dielectrics and Plasmas
Fields, Waves and Electromagnetics
General Topics for Engineers
Photonics and Electrooptics
Power, Energy and Industry Applications
Signal Processing and Analysis
Image color analysis
Phantoms
Microscopy
Color
Image segmentation
Standards
Object segmentation
Microscopic Image Analysis
Biological Response to Electromagnetic Fields
Digital Image Decoloring
Yeast Cell Image Segmentation
Cell Viability Characterization
Language
Abstract
Within the pipeline of microscopic yeast cell image operations, a problem of decoloring is addressed. The approach proposed by Grundland et al. is analyzed and improved. A special color phantom for yeast cell images is constructed. An optimum combination of two controlling parameters of this decoloring method is found for phantom segmentation, by precision and recall characteristics in comparison to Ground truth.