Hough Transform Quiz

What is the key idea behind the Hough Transform?

• Edges must be connected

• Edges vote for possible models

• Only visible lines are detected

• It requires a complete image

In the context of the Hough Transform, what does a point in parameter space represent?

• A shape in the image

• A pixel in the image

• An edge in the image

• A line in image space

How does the Hough Transform handle occluded lines?

• It cannot detect them

• It requires all edges to be visible

• It can detect them through voting

• It uses color information

What is the first step in the Hough Transform algorithm?

• Quantize parameter space

• Set initial parameters

• Create an accumulator array

• Find local maxima

What is a potential problem with the parameterization in the Hough Transform?

• The space of c is always zero

• The space of m is huge

• The space of c is small

• The space of m is limited

What does the accumulator array do in the Hough Transform?

• Stores edge points

• Counts votes for parameters

• Holds the original image

• Tracks noise levels

How does noise affect the Hough Transform's performance?

• It can lead to incorrect votes

• It has no effect

• It improves accuracy

• It reduces the number of edges detected

What is the significance of the local maxima in the accumulator array?

• They indicate noise levels

• They represent detected lines

• They show edge connections

• They are irrelevant to detection

In the polar parameterization, what does the equation x cos(θ) + y sin(θ) = ρ represent?

• A pixel coordinate

• A point in image space

• A line in parameter space

• An edge in the image

Why might a negative value for ρ occur in the Hough Transform?

• It indicates a measurement error

• It is always invalid

• It means the line is not detected

• It represents a line in the opposite direction