Color-based tracking in Drone Programming - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is color-based tracking in drone programming?

Color-based tracking is a method where a drone uses camera input to detect and follow objects based on their specific colors.

intermediate

Why do we convert images from RGB to HSV color space for color tracking?

HSV separates color information (Hue) from brightness (Value), making it easier to detect colors under different lighting conditions.

beginner

What role does thresholding play in color-based tracking?

Thresholding filters the image to keep only pixels within a specific color range, helping the drone isolate the target color.

intermediate

How does contour detection help in color-based tracking?

Contour detection finds the outlines of color regions, allowing the drone to locate and track the shape and position of the colored object.

intermediate

What is a common challenge in color-based tracking for drones?

Changing lighting conditions and background colors similar to the target can cause false detections or loss of tracking.

Which color space is most commonly used for color-based tracking in drones?

A HSV

B RGB

C CMYK

D Grayscale

HSV separates color from brightness, making it easier to detect colors under different lighting.

What does thresholding do in color-based tracking?

A Controls drone speed

B Filters pixels by color range

C Detects edges of objects

D Converts images to grayscale

Thresholding keeps only pixels within a chosen color range to isolate the target.

Why is contour detection important in color-based tracking?

A It finds the shape and position of the colored object

B It changes the drone's altitude

C It adjusts the camera focus

D It filters noise from the image

Contours outline the detected color regions, helping locate the object.

What is a common problem when using color-based tracking outdoors?

A GPS signal loss

B Drone battery drains faster

C Lighting changes affect color detection

D Camera resolution decreases

Outdoor lighting changes can make color detection unreliable.

Which step comes first in color-based tracking?

A Detect contours

B Apply drone commands

C Move the drone

D Convert image to HSV

First, the image is converted to HSV to prepare for color filtering.

Explain the main steps involved in color-based tracking for a drone.

Think about how the drone sees and follows a colored object step by step.

What challenges might a drone face when using color-based tracking and how can they be addressed?

Consider real-world conditions like sunlight and surroundings.

Practice

1. What is the main purpose of color-based tracking in drone programming?

easy

A. To make the drone follow an object by detecting its color

B. To control the drone's altitude using GPS

C. To improve the drone's battery life

D. To send commands to the drone via remote control

Solution

1. Step 1: Understand color-based tracking concept

   Color-based tracking means the drone uses color detection to follow an object.

2. Step 2: Identify the main goal

   The goal is to detect and follow an object by its color, not altitude or battery.

3. Final Answer:

   To make the drone follow an object by detecting its color -> Option A

4. Quick Check:

   Color-based tracking = follow object by color [OK]

Hint: Focus on color detection as the tracking method [OK]

Common Mistakes:

• Confusing color tracking with GPS control
• Thinking it manages battery or remote commands
• Mixing color tracking with altitude control

2. Which of the following code snippets correctly initializes a color filter for red in a drone's tracking system?

easy

A. red_filter = {'lower': (0, 255, 255), 'upper': (10, 100, 100)}

B. red_filter = {'lower': [100, 0, 0], 'upper': [255, 10, 10]}

C. red_filter = {'low': (0, 100, 100), 'high': (10, 255, 255)}

D. red_filter = {'lower': (0, 100, 100), 'upper': (10, 255, 255)}

Solution

1. Step 1: Check correct keys for filter dictionary

   The keys should be 'lower' and 'upper' to define color range.

2. Step 2: Verify value types and ranges

   Values must be tuples with HSV ranges; red_filter = {'lower': (0, 100, 100), 'upper': (10, 255, 255)} uses correct keys and tuples.

3. Final Answer:

   red_filter = {'lower': (0, 100, 100), 'upper': (10, 255, 255)} -> Option D

4. Quick Check:

   Correct keys and tuple values = red_filter = {'lower': (0, 100, 100), 'upper': (10, 255, 255)} [OK]

Hint: Look for 'lower' and 'upper' keys with tuple HSV values [OK]

Common Mistakes:

• Using wrong dictionary keys like 'low' or 'high'
• Using lists instead of tuples for HSV values
• Swapping lower and upper HSV ranges

3. Given the following code snippet for detecting a blue object, what will be printed if the detected object's center is at (150, 200)?

blue_filter = {'lower': (100, 150, 0), 'upper': (140, 255, 255)}
object_center = (150, 200)
if 100 <= object_center[0] <= 140:
    print('Blue object detected at', object_center)
else:
    print('No blue object detected')

medium

A. Blue object detected at (150, 200)

B. SyntaxError

C. No blue object detected

D. RuntimeError

Solution

1. Step 1: Check the condition on x-coordinate

   Condition checks if 100 <= 150 <= 140, which is false because 150 > 140.

2. Step 2: Determine which print executes

   Since condition is false, else block runs printing 'No blue object detected'.

3. Final Answer:

   No blue object detected -> Option C

4. Quick Check:

   150 not in 100-140 range = No detection [OK]

Hint: Check numeric range conditions carefully [OK]

Common Mistakes:

• Assuming 150 is within 100 to 140 range
• Confusing syntax errors with logic errors
• Ignoring else block output

4. The following code is intended to detect a green object and print its position, but it raises an error. What is the error and how to fix it?

green_filter = {'lower': (40, 50, 50), 'upper': (80, 255, 255)}
object_center = None
if green_filter['lower'][0] <= object_center[0] <= green_filter['upper'][0]:
    print('Green object at', object_center)
else:
    print('No green object detected')

medium

A. SyntaxError due to incorrect dictionary keys; fix keys to 'low' and 'high'

B. TypeError because object_center is None; fix by assigning a tuple to object_center

C. IndexError because green_filter keys are missing; add keys

D. No error; code runs correctly

Solution

1. Step 1: Identify the error cause

   object_center is None, so accessing object_center[0] causes TypeError.

2. Step 2: Fix the error

   Assign a tuple like (x, y) to object_center before using it in condition.

3. Final Answer:

   TypeError because object_center is None; fix by assigning a tuple to object_center -> Option B

4. Quick Check:

   None used as index causes TypeError [OK]

Hint: Check variable types before indexing [OK]

Common Mistakes:

• Ignoring NoneType indexing error
• Changing dictionary keys incorrectly
• Assuming code runs without error

5. You want the drone to follow a yellow object but only if its detected center's y-coordinate is above 100. Which code snippet correctly implements this condition using color-based tracking?

yellow_filter = {'lower': (20, 100, 100), 'upper': (30, 255, 255)}
object_center = (120, 150)

# Choose the correct condition to check

hard

A. if yellow_filter['lower'][0] <= object_center[0] <= yellow_filter['upper'][0] and object_center[1] > 100:
print('Following yellow object')

B. if yellow_filter['lower'][1] <= object_center[1] <= yellow_filter['upper'][1] and object_center[0] > 100:
print('Following yellow object')

C. if yellow_filter['lower'][0] <= object_center[1] <= yellow_filter['upper'][0] and object_center[0] > 100:
print('Following yellow object')

D. if yellow_filter['lower'][1] <= object_center[0] <= yellow_filter['upper'][1] and object_center[1] > 100:
print('Following yellow object')

Solution

1. Step 1: Understand HSV and coordinate roles

   yellow_filter keys 'lower' and 'upper' define hue range at index 0; object_center[0] is x, object_center[1] is y.

2. Step 2: Check condition for hue and y-coordinate

   Hue check uses object_center[0] between lower and upper hue; y-coordinate must be > 100.

3. Final Answer:

   if yellow_filter['lower'][0] <= object_center[0] <= yellow_filter['upper'][0] and object_center[1] > 100: print('Following yellow object') -> Option A

4. Quick Check:

   Hue range on x and y > 100 condition = if yellow_filter['lower'][0] <= object_center[0] <= yellow_filter['upper'][0] and object_center[1] > 100: print('Following yellow object') [OK]

Hint: Match hue with x, check y > 100 separately [OK]

Common Mistakes:

• Mixing x and y coordinates in conditions
• Using wrong indices for hue or saturation
• Checking y-coordinate against hue range