Edge detection is one of the most important tasks in image processing. Image segmentation, registration, and identification are based on edge detection. In this design fuzzy logic approach is proposed for edge detection. The rule-based approach offers the most advantages such as giving permission to adapt some parameters easily. The edges thickness can be changed easily by adding new rules or changing output parameters. That is to say, the rule-based approach has a flexible structure which can be adapted any time or anywhere easily and fuzzy approach produces a nice result. The steps followed in design are listed below,

Step 1:  Select image 
Step 2: Split image into 3x3 block
Step 3: Find the difference between the mean of the block and pixel values in this block. d1, d2 ,d3, d4,d6,d7,d8,d9 are pixel difference value.
Step 4: Similar process applying for whole image block.
Step 5: Declare fuzzy structure name.
Step 6: Declare the input membership function.  Here three-member ship functions available for d1 value
    1, Zero level
    2, Non-zero level1
    3, Non-zero level2
Step 7:  Similar to d2, d3, d4, d6, d7, d8, d9 input
Step 8: Declare output membership function. Here only two-member functions available for output
    1, Black
    2, White
Step 9: Create a rule matrix based on different conditions
Step 10: Combine fuzzy structure, input membership function, output membership function, and rule matrix.
Step 11: Evaluate this fuzzy structure using image pixel difference values.
Step 12: Finally get black or white pixel value depends on the image pixel.

Reference Paper-1: A New Fuzzy Approach for Edge Detection

Author’s Name: Yasar Becerikli and Tayfun M. Karan

Source: Conference Paper in Lecture Notes in Computer Science


Reference Paper-2: Edge detection techniques using Fuzzy Logic

Author Name: Essa Anas

Source: IEEE-3rd International Conference on Signal Processing and Integrated Networks (SPIN)


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