Real-time Color Detection Using Webcam with OpenCV and Python

In this article, we explore how to perform color detection using a webcam. Color detection represents one of the fundamental applications in computer vision technology. Through this technique, we can classify pixels in images into different color categories. This technology finds applications across various domains including robotic vision, autonomous driving, and medical diagnostics. In this implementation, we demonstrate how to achieve color detection using Python programming language and OpenCV library. The process begins with initializing the webcam connection using cv2.VideoCapture(0) to access the default camera. We then capture real-time frames and convert them from BGR to HSV color space using cv2.cvtColor() function, as HSV provides better color segmentation capabilities compared to RGB. Following this, we define color thresholds using cv2.inRange() function to create a binary mask that isolates specific color ranges based on hue, saturation, and value parameters. The mask is applied to the original image using bitwise operations to highlight detected colors. Finally, we display both the original video feed and the color-detected output using cv2.imshow() for comparative analysis. This approach helps beginners understand the fundamental principles of color detection and serves as a practical foundation for real-world applications.