11 Questions
What is the primary function of the gradient operator in image processing?
To detect abrupt changes in image intensity
What is the purpose of the Laplacian operator in image processing?
To detect local extreme values in an image
What is the mathematical representation of the Laplacian operator?
∂²f/∂x² + ∂²f/∂y²
What is the advantage of using the discrete Laplacian operator in image processing?
It is more computationally efficient than the continuous Laplacian operator
Why is the zero-crossing method sensitive to noise?
Because it is based on the second derivative of the image function
What is the primary effect of 1st order derivatives on an image?
Thicker edges
What is the primary advantage of the Canny Edge Detector?
Low error rate of detection and good localization of edges
What is the purpose of the non-maximum suppression stage in the Canny Edge Detector?
To find the peaks in the image gradient
What is the result of applying a 2nd order derivative to an image?
Double response at step changes in gray level
What is the name of the algorithm that produces a single response for a single edge pixel?
Canny Edge Detector
What is the purpose of the hysteresis thresholding stage in the Canny Edge Detector?
To locate edge strings
This quiz covers the concepts of image noise, gradients, and Laplacian operators in image processing. It focuses on the mathematical aspects of image processing, including first and second-order derivatives, and the discrete Laplacian operator. Test your understanding of these fundamental concepts in image processing.
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