1. 1 A new approach to morphological color image processing G. Louverdis, M.I. Vardavoulia, I.Andreadis ∗, Ph. Tsalid, Pattern Recognition 35 (2002) 1733–1741 報告 : 趙國宇

2. 2 Abstract Base on concepts of grayscale morphology processing That is vector preserving and provides improved results in many morphological applications Noise removal, Edge detection and Skeleton extraction

3. 3 Introduction(1/) Vector Erosion( 侵蝕 ) and Dilation( 擴張 )

4. 4 Introduction(2/) A new vector ordering in the HSV color space vector ordering scheme 1.sorted from vectors with the smallest v to vectors with the greatest v. 2.having the same value of v, sorted from vectors with the greatest s to vectors with the smallest s. 3.having the same value of v and s, sorted from vectors with the smallest h to vectors with the greatest h.

5. 5 Introduction(3/) Vector ordering

6. 6 Introduction(4/) Definitions of new infimum and supremum operators

7. 7 Introduction(5/) Morphological operators for color images 1.Basic definitions f(x): D[f]={x: f(x) ∈ HSV}: If f(k)=(hkf; skf; vkf) and g(k)=(hkg; skg; vkg); k ∈ R2

8. 8 Introduction(5/) Morphological operators for color images 2.Vector erosion 3.Vector dilation 4.Basic properties of vector erosion and dilation a. The adjunction property

9. 9 Introduction(6/) Morphological operators for color images 5. Other properties a. (Extensivity–antiextensivity) b. (Increasing–decreasing) c. (Duality) d. (Translation invariance)

10. 10 Introduction(7/) Morphological filtering for color images 1.It is based on opening (erosion followed by dilation) and closing (dilation followed by erosion) operators.

11. 11 Introduction(8/)

12. 12 Example of morphological filtering (a) original image “Lenna”, (b) image corrupted by spike noise, (c) result of erosion,(d) result of opening,

13. 13 Example of morphological filtering (e) result of performing dilation on the opening, (f) final result showing the closing of the opening.

14. 14 1.Boundary extraction Other applications Application of the boundary extraction algorithm: (a) original image, (b) resultant image.

15. 15 Other applications 2.Color image skeletonization Application of the skeletonization algorithm: (a) original image, (b) resultant image.