LAB 2
Edge and Line Detection:
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Edge and Line Detection operators applied different convolution mask. This
might be due to several factors like:
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Image brightness
Orientation of edges (direction)
Presence of edge at each point
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Edge detection is first step to find line. It finds complex object boundaries by
marking potential edge points where rapid changes happen. After edge have been
mark then line or outline of images can be form. (Contour image)
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Noise can interrupt the edge and line detection, and is proposed to be minimized
or eliminate. Other than that the level of brightness could also corrupt an image.
Both the problem above along with the sensitivity of the detector will produce
“false edges”. Detectors, which are sensitive, can accidentally include noise, as an
edge (false edges) while the less sensitive ones might not detect the real edges.
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A larger mask will be less sensitive to noise
A lower gray level threshold will reduce noise
For lab 2 test each one of the operators for edge and line detection
1. If pre-filter and post threshold value is set to none, which of the following
operator (Kirsch,Piramid,Robinson) which do you think best represent the
contour image of the image plane.ras?
2. Enter the value 20, 80, 100 and 120 to the post threshold value and applied it
each with the operators (Kirsch,Piramid,Robinson) to the image plane.ras.
Write down your observation on the changes that happened.
3. If pre-filter and post threshold value is set to none, and kernel size is 3 which
of the following operator (Sobel and prewitt) which do you think best
represent the contour image of the image plane.ras? Then try both operator out
with kernel size 5, and 7 what can you see?
4. Enter the value 20, 80, 100 and 120 to the post threshold value and applied it
each with the operators (Sobel and prewitt)to the image plane.ras. Use kernel
size 3. Write down your observation on the changes that happened.
5. If pre-filter and post threshold value is set to none, which of the following
operator (Roberts,Laplacian) which do you think best represent the contour
image of the image plane.ras?
6.
i. Add some salt and pepper noise to the original image.
(Restoration->Noise-Salt and Pepper).
ii. Perform edge detection on the image contaminated by the noise.
Use Sobel and prewitt.(pre-filter and post threshold = none)
iii. What is the effect of noise in edge detection? Can see the “false
edge”? Base on the principle of edge detection, can you explain why the
presence of noise would result in “false edge" detection?
iv. Try to adjust the threshold value in order to minimize the “false edge”
detection. What is the negative side effect in minimizing “false edge” by
adjusting the threshold value?
v. With minimum window size (sharpest edge), adjust the threshold value
until the level “just before” the “main edge” starts to disappears.
vi. Stay at that threshold value and adjust the kernel size to obtain
sharpest possible main edge with minimum possible
“false edge” detection.