Multiple Color Detection in Real-Time using Python-OpenCV

For a robot to visualize the environment, along with the object detection, detection of its color in real-time is also very important.

Why this is important? : Some Real-world Applications

• In self-driving car, to detect the traffic signals.
• Multiple color detection is used in some industrial robots, to performing pick-and-place task in separating different colored objects.

This is an implementation of detecting multiple colors (here, only

red

,

green

and

blue

colors have been considered) in real-time using Python programming language.

Python Libraries Used:

• NumPy
• OpenCV-Python

Work Flow Description:

• Step 1:
• Input: Capture video through webcam.
• Step 2:
• Read the video stream in image frames.
• Step 3:
• Convert the imageFrame in BGR(RGB color space represented as three matrices of red, green and blue with integer values from 0 to 255) to HSV(hue-saturation-value) color space.
• Hue
• describes a color in terms of
• saturation
• , represents the amount of gray color in that color and
• value
• describes the brightness or intensity of the color. This can be represented as three matrices in the range of 0-179, 0-255 and 0-255 respectively.
• Step 4:
• Define the range of each color and create the corresponding mask.
• Step 5:
• Morphological Transform: Dilation, to remove noises from the images.
• Step 6:
• bitwise_and between the image frame and mask is performed to specifically detect that particular color and discrad others.
• Step 7:
• Create contour for the individual colors to display the detected colored region distinguishly.
• Step 8:
• Output: Detection of the colors in real-time.

Below is the implementation.

Output: