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Lecture - Morphology

# Lecture - Morphology - EE4780 Morphological Image...

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EE 4780 Morphological Image Processing

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Bahadir K. Gunturk 2 Example Two semiconductor wafer images are given. You are supposed to determine the defects based on these images.

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Bahadir K. Gunturk 4 Example Absolute value of the difference
Bahadir K. Gunturk 5 Example >> b = zeros(size(a)); >> b(a>100) = 1; >> figure; imshow(b,[ ]);

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Bahadir K. Gunturk 6 Example >> c = imerode(b,ones(3,3)); >> figure; imshow(c,[]);
Bahadir K. Gunturk 7 Example >> d = imdilate(c,ones(3,3)); >> figure; imshow(d,[]);

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Bahadir K. Gunturk 8 Mathematical Morphology We defined an image as a two-dimensional function, f(x,y), of discrete (or real) coordinate variables, (x,y). An alternative definition of an image can be based on the notion that an image consists of a set of discrete (or continuous) coordinates.
Bahadir K. Gunturk 9 Morphology B = {(0,0), (0,1), (1,0)} A = {(5,0), (3,1), (4,1), (5,1), (3,2), (4,2), (5,2)} A binary image containing two object sets A and B

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Bahadir K. Gunturk 10 Morphology Sets in morphology represent the shapes of objects in an image. For example, the set A = {(a1,a2)} represents a point in a binary image. The set of all black pixels in a binary image is a complete description of the image.
Bahadir K. Gunturk 11 Mathematical Morphology Morphology is a tool for extracting and processing image components based on shapes. Morphological techniques include filtering, thinning, pruning.

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Bahadir K. Gunturk 12 Basic Set Operations
Bahadir K. Gunturk 13 Some Basic Definitions Let A and B be sets with components a=(a1,a2) and b=(b1,b2), respectively. The translation of A by x=(x1,x2) is A + x = {c | c = a + x, for a A} The reflection of A is A r = {x | x = -a for a A} The complement of A is A c = {x | x A} The union of A and B is A

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