ABSTRACT
This project presents an interactive real-time color detection system using Python and OpenCV, aimed at accurately identifying colors from a live video stream. The system captures video input from a webcam and allows the user to click on any pixel within the frame to retrieve its RGB values. By referencing a predefined color dataset, the system matches the clicked pixel’s RGB values to the closest named color and displays the corresponding color name and hexadecimal code on the screen. This facilitates a deeper understanding of digital color representation and can be used in various practical applications, including UI/UX design, educational tools, and accessibility features for individuals with color vision deficiency. The integration of mouse-based interaction with efficient color recognition makes this tool both intuitive and robust for real-time environments.
Keywords: Real-Time Color Detection, OpenCV, RGB to Color Name Mapping, Computer Vision, Human-Computer Interaction, Webcam Image Processing, Color Recognition, Color Picker Tool, Image Analysis


OBJECTIVES
The primary objective of this project is to develop a real-time color detection system using Python and OpenCV. The specific goals include:
1. To capture live video feed from a webcam and allow user interaction through mouse clicks.
2. To extract and display the RGB values of the pixel selected by the user.
3. To match the extracted RGB values with a predefined dataset to identify the closest named color.
4. To display the color name, RGB values, and hexadecimal code on the screen in real-time.
5. To enhance usability through adaptive text color for readability and smooth graphical overlay.