Hue Spectrum visualizer using python with OpenCV

Color analysis is a significant source in many image processing processes consisting of automotive vehicle navigation, protest detection, traffic sign recognition, skin color analysis, and object tracking. The approach adopted in this study mainly relies on the ability to locate the color name right at the center of the camera frame and determine the objects of red, green, and blue colors using the bounding box property. By rating the amount of red, green and blue of each pixel's outfits, the colors of these pixel are revealed. Next, all objects of interest that fall within the video segment of interest are detected and located using rectangular boundary boxes based on the HSV color model. The process used in this process entails the use of a dataset that has a tabular form with data on color names and its values to arrive at the best match. The values of Red, Blue, and Green (RGB) as well as color names of each pixel are extracted, providing the means to track the three separate colors in the video stream. When a color is not detected in the reference data but observed in the real-time stream, a box surrounds the mentioned color: the color name is written above the box. It enhances the approaches to recognition of color and also provides significant improvements in the field of robotics. The application of these techniques generally involves the use of the OPENCV software library together with the PYTHON programming language.