Assume that a bi-level input image x[n, n2] of 512x512 as shown below, where the dark...
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Assume that a bi-level input image x[n₁, n2] of 512x512 as shown below, where the dark region has amplitude of 50 and the white foreground has amplitude of 100. -1 -2 0 2 -1 0 1 Sobel filter_1 0 1 0 -1 0 -1 0 -2 -1 0 1 Sobel filter 2 -1 0 4 0 -1 0 1 2 Image Laplacian filter 1) Use Sobel edge detector on this image, which will produce two filtered images G₁(x[n1, n2]) and G₂(x[n1, n2]). Sketch your output images. Note that each actual edge may result in single, double, triple or more lines depending on different edge detectors. You should specify the number of lines for each edge, as well as the amplitude value for each of these lines. (Hint: refer to "edge-detc.pdf".) 2) Use Laplacian filter on this image and sketch your output image highlighting all pixels with none zero amplitudes. 3) Comment on the difference between these two types of edge detectors. Assume that a bi-level input image x[n₁, n2] of 512x512 as shown below, where the dark region has amplitude of 50 and the white foreground has amplitude of 100. -1 -2 0 2 -1 0 1 Sobel filter_1 0 1 0 -1 0 -1 0 -2 -1 0 1 Sobel filter 2 -1 0 4 0 -1 0 1 2 Image Laplacian filter 1) Use Sobel edge detector on this image, which will produce two filtered images G₁(x[n1, n2]) and G₂(x[n1, n2]). Sketch your output images. Note that each actual edge may result in single, double, triple or more lines depending on different edge detectors. You should specify the number of lines for each edge, as well as the amplitude value for each of these lines. (Hint: refer to "edge-detc.pdf".) 2) Use Laplacian filter on this image and sketch your output image highlighting all pixels with none zero amplitudes. 3) Comment on the difference between these two types of edge detectors.
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Dilation It add pixel at the object boundary It Expands the original Image fh s Max x h 8x OO O O O ... View the full answer
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