Intelligent Simulation Framework for RGB Color Detection and Mixing for Accurate Color Synthesis

Abstract

The detection of color and synthesis of colors play a crucial role in computer vision, textile technology, and digital imaging. Traditional methods involve the use of either physical sensors or thresholding methods that depend completely on the environment. The problems associated with the traditional methods are variability of illumination, dependence on physical sensors, and high costs due to hardware usage. In the proposed work, the method uses an intelligent software-based simulation approach to detect and synthesize red, blue, and green colors. The proposed system has been developed using Python along with libraries like OpenCV, NumPy, Matplotlib, and Streamlit to support real-time color detection, visualization, and RGB blending. Through experimental results, it is found that the time delay is less than 100 milliseconds with more than 25 frames per second. By eliminating the need for physical sensors, the method enhances accuracy and can be used for industrial purposes and textile color detection. Keywords: image processing; Color detection; RGB mixing; Simulation framework; OpenCV.