
24AI2002 - Corner Detection Quiz
Authored by Dinesh Peter
Computers
University
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10 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Identify the correct description of a "corner" in an image.
A point where image intensity is constant
A point where two edges meet with intensity changing in one direction only
A point where intensity changes in two or more directions, such as the intersection of edges
A point with no gradient in any direction
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What does it indicate when both x and y gradients around a point are large?
A flat region
An edge
A corner
Noise
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What role do the eigenvalues λ₁ and λ₂ of the Harris matrix (M) play in corner detection?
Both small → Edge; Both large → Flat
One large and one small → Corner
Both large → Corner; One large, one small → Edge; Both small → Flat
Eigenvalues are not used
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
The Harris corner response function is given by R = det(M) – k·trace(M)². What kind of regions result when R is high?
Flat regions
Edges
Corners
Regardless of R, it's never a corner
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the purpose of non-maximum suppression in corner detection?
To blur the image
To keep only the strongest corner in a local neighborhood
To convert edges to corners
To equalize the histogram of corner values
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
In the Harris corner detection algorithm, what does a high corner response map indicate?
Likely corners
Likely edges only
Flat areas
Regions of high noise
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the main difference between edges and corners in terms of gradient change?
Edges have a change in intensity in multiple directions, while corners have change in one direction
Corners have intensity change in two or more directions; edges only in one
Edges are detected by color; corners are detected by shape
Corners are always brighter than edges
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