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HCI / CprE / ComS 575: Computational Perception

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1 HCI / CprE / ComS 575: Computational Perception
Instructor: Alexander Stoytchev

2 Mathematical Morphology
HCI/CprE/ComS 575: Computational Perception Iowa State University, Ames, IA Copyright © Alexander Stoytchev

3 Reading for Today’s Lecture
Haralick and Shapiro (1993). Computer and Robot Vision, "Chapter 5: Mathematical Morphology," Addison-Wesley.

4 Readings for Next Lecture
Start reading the OpenCV Book. OpenCV Tutorial

5 Reading for Next Week Jain, Kasturi, and Schunck (1995). Machine Vision, ``Chapter 4: Image Filtering,'' McGraw-Hill, pp Burt, P., and Adelson, E. (1983) “The Laplacian Pyramid as a Compact Image Code,” IEEE Transactions on Communication, Vol. COM-3l, No. 4, pp , April 1983.

6 Images and Structuring Elements
origin [Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 2]

7 Images and Structuring Elements
origin [Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 2]

8 Images and Structuring Elements
origin [Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 2]

9 Images and Structuring Elements
origin [Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 2]

10 Images and Structuring Elements
origin [Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 2]

11 And so on …. until we reach the first pixel of the larger image

12 Images and Structuring Elements
origin [Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 2]

13 Erosion Erosion of an image by a structuring element results in an image that gives all locations where the structuring element is contained in the image.

14 Examples of Pixels that will be deleted
[Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 2]

15 Examples of Pixels that will be deleted
[Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 2]

16 Erosion Results [Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 2]

17 Another Example [Haralick and Shapiro (1993). “Computer and Robot Vision,” Ch. 5 ]

18 Yet Another Example [Haralick and Shapiro (1993). “Computer and Robot Vision,” Ch. 5 ]

19 Dilation The union of the translations of the image A by the 1 pixels of the image B is called the dilation of A by B.

20 Dilation Example [Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 2]

21 Examples of pixels that will be added
[Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 2]

22 Examples of pixels that will be added
[Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 2]

23 Examples of pixels that will be added (in fact, all black pixels of the SE are added)
[Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 2]

24 Dilation Results

25 [Haralick and Shapiro (1993). “Computer and Robot Vision,” Ch. 5 ]

26 [Haralick and Shapiro (1993). “Computer and Robot Vision,” Ch. 5 ]

27 Notation Erosion Dilation
[Jain, Kasturi, and Schunck (1995). Machine Vision, Ch. 2]

28 Real Examples

29 Segmenting the Body and Handle
[Haralick and Shapiro (1993). “Computer and Robot Vision,” Ch. 5 ]

30 Horizontal & Vertical Lines
[Haralick and Shapiro (1993). “Computer and Robot Vision,” Ch. 5 ]

31 [Haralick and Shapiro (1993). “Computer and Robot Vision,” Ch. 5 ]

32 Circles & Lines [Haralick and Shapiro (1993). “Computer and Robot Vision,” Ch. 5 ]

33 Clustering [Haralick and Shapiro (1993). “Computer and Robot Vision,” Ch. 5 ]

34 Chip [Haralick and Shapiro (1993). “Computer and Robot Vision,” Ch. 5 ]

35 [Haralick and Shapiro (1993). “Computer and Robot Vision,” Ch. 5 ]

36 Algebraic Relations [Haralick and Shapiro (1993). “Computer and Robot Vision,” Ch. 5 ]

37 Matlab Demos

38 THE END


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