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Worksheetscomputer vision Quiz
Total questions: 20
Worksheet time: 20mins
You want to crop a part of one image, resize it, and blend it with another image so both are partially visible. Which OpenCV functions and parameters would you need?
a) Cropping + cv2.addWeighted()
b) Cropping + cv2.add()
c) cv2.merge() + Cropping
d) cv2.bitwise_or() + Cropping
You apply Gaussian Blur before Canny edge detection on a grayscale image. Which problem is this sequence trying to avoid?
a) Missing strong edges
b) Detecting noise as edges
c) Losing image brightness
d) Changing color representation
You are designing a shape-tracking app that requires edge detection and real-time object boundary drawing. Which two main OpenCV features would you combine?
a) Filters + Color conversion
b) Edge detection + Contours
c) HSV masking + Gaussian Blur
d) Cropping + Rotation
You want to compare the smoothing effects of three filters from the slides. Which combination of filters should you apply in sequence to see clear differences?
a) Averaging → Gaussian → Median
b) Laplacian → Sobel → Canny
c) HSV mask → Contours → Sobel
d) Resize → Merge → Rotate
You are processing a webcam feed to detect a moving blue object and draw a rectangle around it. Which two main steps from the slides are required?
a) HSV masking + Contours
b) Gaussian Blur + Sobel
c) Laplacian + Merge
d) Cropping + Resize
You need to detect vertical edges in a resized grayscale image and then highlight them in color on the original image. Which sequence works?
a) Resize → Grayscale → Sobel Y → Overlay on original
b) Sobel X → Merge → HSV
c) Laplacian → HSV mask
d) Grayscale → Gaussian Blur → Canny
You want to detect objects of a certain color in HSV and then find their exact shape outlines. Which two methods from the slides should you combine?
a) Masking + Contours
b) Sobel + Median Blur
c) Laplacian + AddWeighted
d) Gaussian Blur + Cropping
You want to make a real-time drawing board that uses color tracking. Which combination from the slides is most essential?
a) HSV masking + Contours + Drawing functions
b) Sobel + Gaussian Blur + Merge
c) Laplacian + AddWeighted + Resize
d) Grayscale + Median Blur + Rotate
You apply Median Blur to a grayscale image and then run Canny edge detection. Why might this give better results than applying Canny directly?
a) Removes small noise before edge detection
b) Makes edges thicker
c) Increases brightness
d) Changes the image resolution
You run Canny edge detection on a noisy HSV mask without blurring first. What is the most likely problem you’ll face?
a) Many false edges from noise in the mask
b) Edges will be too thin
c) Only vertical edges will be detected
d) Edges will disappear completely
You want to detect a red ball in a live feed, draw a rectangle around it, and overlay text showing its coordinates. Which is the correct set of operations?
a) HSV mask → Contours → cv2.rectangle() → cv2.putText()
b) Sobel → Canny → cv2.rectangle()
c) Grayscale → Laplacian → cv2.putText()
d) HSV mask → Gaussian Blur → Laplacian
You apply Sobel in X direction after resizing the image and converting it to grayscale. How will resizing impact the Sobel result?
a) Smaller details may be lost but processing is faster
b) Edges will remain identical
c) Edges will invert colors
d) It will increase noise
You merge two grayscale images using cv2.addWeighted() and then apply Canny. What’s the main advantage of doing this?
a) Edge detection on combined brightness details from both images
b) Better color tracking
c) Higher resolution output
d) Stronger saturation
You want to create a binary mask for blue objects and detect their edges in one pipeline. Which correct sequence comes from the slides?
a) Convert BGR to HSV → Create mask → Canny
b) Canny → HSV mask → Gaussian Blur
c) Median Blur → Convert to HSV → Create mask
d) Gaussian Blur → Canny → HSV
You apply Laplacian to detect edges and then immediately pass the result to cv2.putText(). Why might this be done?
a) Label the detected edge image with information
b) Increase edge sharpness
c) Convert edges to grayscale
d) Merge edges into background
You are tracking two colors at once in HSV but they overlap in certain lighting. Which method from the slides can help separate them?
a) Use two different masks and combine them with bitwise operations
b) Convert to grayscale and threshold
c) Apply Laplacian before masking
d) Resize images before masking
You apply Laplacian to detect edges, then overlay them on the original color image. What is the benefit of this combination?
a) See edges clearly while keeping original colors
b) Blur edges
c) Remove colors entirely
d) Change color intensity
ou want to detect red objects using HSV, but lighting conditions change rapidly. Which extra step should you add before masking to improve detection stability?
a) Apply Gaussian Blur
b) Convert to Grayscale
c) Apply Canny
d) Increase image resolution
You merge two images using cv2.addWeighted() after converting both to grayscale. Why might this be done?
a) To reduce complexity and blend brightness values
b) To make colors appear more natural
c) To increase color contrast
d) To improve contour detection
You create a binary mask in HSV and then apply contours to it. What does this combination achieve?
a) Detects shape outlines of the chosen color
b) Creates a grayscale version of the image
c) Sharpens image edges
d) Blends two images together
