Fuzzy Mathematical Morphology - Medical Image Processing: Advanced Fuzzy Set Theoretic Techniques - page 208

⎡ ⎤

⎥

⋅ −
+−⋅ +−−

Ay By x
Ay By xAyByx

() ( )

DAB (,) up =

⎢

( 1 ) (() ( ) ( )( ))

γ γ ⋅ −

yS ∈

The value of γ = 0.2 is chosen by the trial-and-error method. Next, the edge
image is created by taking the difference of the dilation and erosion, and
then the image is binarized to obtain a binarized edge image.

Example 9.1
Three results are shown on medical images in Figures 9.1 through 9.3.
Results on fuzzy morphology using Lukasiewicz operator and intuition-
istic fuzzy morphology using Hamacher t -operators are shown.

(a) (b) (c)

FIGURE 9.1
(a) Blood cell image, (b) edge image using Lukasiewicz operator and (c) edge image using
Hamacher t -operator utilizing the intuitionistic fuzzy approach.

(a) (b) (c)

FIGURE 9.2
(a) Noisy CT scan brain image, (b) edge image using Lukasiewicz operator and (c) edge image
using Hamacher t -operator utilizing the intuitionistic fuzzy approach.