Classification of total carotene and quality of chili pepper (Capsicum frutescens) based on image analysis

Abstract

The process of sorting the chili pepper (Capsicum frutescens) is done physically by using the human eye, based on the visual color uniformity of its skin. This method is not effective and efficient. This study aims to identify the total content of carotene in chili pepper using the color and textural features approach. Color feature extraction used is the value of RGB, HSV, HSL, XYZ, CMY, CMYK, Lab, LUV, LCH, grey color, and 10 textural features from each color-space. The feature extraction results were used to identify the total carotene content by the image analysis method. The image of chili peppers used was 360, consisting of 300 training data and 60 test data. Classification test results with a level of 20% produce the best parameters as an indicator of total carotene chili pepper i.e. hue mean features with a range for quality A (55.04 > hue mean > 32.15), quality B (19.80 > hue mean > 12.21), quality C (3.55 > hue mean > 1.93), and 80% accuracy using the confusion matrix and mean square error (MSE).

Rapid and visual identification of β-lactamase subtypes for precision antibiotic therapy

“…A color recognizer software was installed in the smartphone to quantitatively analyze the color changes of the sensors. The color recognizer offers 8 color modes: digital equipment corporation (DEC), hexadecimal (HEX), alpha-red-green-blue (ARGB), cyan-magenta-yellow-key (CMYK), CIELAB (Lab), hue-saturation-value (HSV), hue-saturation-lightness (HSL), and luma-chroma (YUV) 44 , 45 . After investigating the negative, weak positive, and positive results on three randomly-selected sensors (Supplementary Fig.…”