1. 7.1 Morfologi untuk Pengolahan Citra : Thickening, Skeleton

2. Thickening Thickening -the morphological dual of thinning -Denote by
The structuring element with the same form as those shown in thinning, but with all 1’s and 0’s interchanged.

3. Thickening
However a separate algorithm for thickening is seldom used in practices, instead, the usual procedure is to thin the background, and then complement the result.
Give A, get C=Ac, thin C, and then get Cc.
This procedure may result in some disconnected points, usually it follows by a simple postprocessing step to them.

4. Skeletons

5. Skeletons Skeletons -Define in terms of erosions and openings
-Denote by:
Sk(A)=(AkB)- (AkB) ◦B
(A kB)=(…(A B) B) …) B)
K=max{k|(A B) }
K is the last iterative step before A erodes to an empty set.
Also, A can be reconstructed from these subsets:

6. Skeletons Error in the book: Chinese edition page 442
or English edition page 545

7. Skeletons MATLAB code: y=bwmorph(x,’skel’,inf); Skeletons.m
Binary fingerprint image
Skeleton image
MATLAB code: y=bwmorph(x,’skel’,inf);
Skeletons.m

8. Summary
Dilation, Erosion, Opening, Closing, Skeletons, Boundary extraction
Region filling
Thinning, Thickening
Convex hull
Pruning

9. Summary

10. Summary

11. Summary

12. Summary

13. Daftar Pustaka
Kadir, Abdul, Susanto,A., “Pengolahan Citra, Teori Dan Aplikasi”, Andi, Yogyakarta, 2013.