Color Object Tracker

Track colored objects in real-time using HSV color space.

View Source Code

Overview

Track objects by their color in real-time video. Perfect for robotics, games, and interactive applications.

Key Techniques:

  • HSV color space conversion
  • Color range thresholding
  • Contour detection
  • Centroid tracking

How It Works 

Frame → HSV Convert → Color Mask → Find Contours → Track Center
   ↓         ↓            ↓              ↓             ↓
[BGR]    [H,S,V]      [Binary]     [Largest]     [x, y]

Why HSV?

HSV (Hue, Saturation, Value) separates color from brightness:

  • Hue: The actual color (0-180 in OpenCV)
  • Saturation: Color intensity (0-255)
  • Value: Brightness (0-255)

This makes color detection robust to lighting changes.

Key OpenCV Functions 

# Convert BGR to HSV
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

# Create color mask
mask = cv2.inRange(hsv, lower_bound, upper_bound)

# Clean up mask
mask = cv2.erode(mask, kernel, iterations=2)
mask = cv2.dilate(mask, kernel, iterations=2)

# Find largest contour
contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
largest = max(contours, key=cv2.contourArea)

# Get center using moments
M = cv2.moments(largest)
cx = int(M['m10'] / M['m00'])
cy = int(M['m01'] / M['m00'])

Default Color Ranges

Color H Low H High S Range V Range
Red 0-10, 170-180 - 100-255 100-255
Green 35 85 100-255 100-255
Blue 100 130 100-255 100-255
Yellow 20 35 100-255 100-255

Controls

Key Action
r Track red
g Track green
b Track blue
y Track yellow
+/- Adjust threshold
s Save screenshot
q Quit

Running the Application 

python curriculum/applications/02_color_tracker.py

Official Documentation