Selecting the Function of Color Space Conversion RGB / HSL to Wavelength for Fluorescence Intensity Measurement on Android Based Applications

Abstract

Molecular biology-based tests are widely used to monitor various activities, such as molecular interaction dynamics, cell health, and in other health studies. At present molecular biology detection technology is widely available in city center laboratories, but this does not happen in small clinics and in remote areas. For this reason, a method called point of care (POC) was developed, which is a medical diagnostic test near a place of care that can provide fast results. Fluorescence is one method of labeling samples that are widely used in point of care activities. Recent research has detected fluorescence with quite good results, but the detection done is mostly based on RGB color space without regard to wavelength. In fact, wavelength is an important factor in fluorescence detection where using wavelength, the detection results can show the level of intensity of the light produced by the fluorescence sample. In this research, the curve fitting function is created which can convert the RGB value in an image or image to a wavelength value. From 3 fitting curves with RGB, HSV, and hue data, the function with the smallest mean squared error and the smallest root mean squared error will be selected. Next, using the best fitting curve function will read the wavelength value of a fluorescence sample photo. The results of this experiment show that the combination of the use of the fitting curve function obtained from HSV data and the fitting curve obtained from hue produces the most optimal error results, with a mean squared error (MSE) value of 367,373, compared to the MSE results of the RGB fitting curve with value 3908.1, HSV fitting curve with a value of 593.6, and hue fitting curve which is worth 1456.62.