Extraction method of filtration detail characteristics of Sobel operator for presenting fabric grain
A Sobel operator, fabric texture technology, applied in computing, image data processing, computer parts and other directions, can solve the problem of not clearly defining the meaning of boundary points, insufficient texture representation, not considering the distribution of boundary points, etc.
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Embodiment 1
[0072] (1) Get the fabric image, such as figure 2 shown.
[0073] (2) Use one-dimensional FFT to calculate the period of any row of grayscale data in the original image, and obtain the column basic period P 1 = 6 pixels.
[0074] (3) Use one-dimensional FFT to calculate the period of any column of grayscale data in the original image, and obtain the basic period P of the row 2 = 4 pixels.
[0075] (4) Implement Sobel operator horizontal filtering on the original image to obtain the filtered image as image 3 shown.
[0076] (5) Implement Sobel operator vertical filtering on the original image to obtain the filtered image as Figure 4 shown.
[0077] (6) According to image 3 and P 2 And combined with Shannon entropy calculation formula
[0078] X ( s ) = - Σ i s i 2 log 2 ...
Embodiment 2
[0085] (1) Get the fabric image, such as Figure 5 shown.
[0086] (2) Use one-dimensional FFT to calculate the period of any row of grayscale data in the original image, and obtain the column basic period P 1 = 20 pixels.
[0087] (3) Use one-dimensional FFT to calculate the period of any column of grayscale data in the original image, and obtain the basic period P of the row 2 = 11 pixels.
[0088] (4) Implement Sobel operator horizontal filtering on the original image to obtain the filtered image as Figure 6 shown.
[0089] (5) Implement Sobel operator vertical filtering on the original image to obtain the filtered image as Figure 7 shown.
[0090] (6) According to Figure 6 and P 2 Combined with the calculation formula of logarithmic energy entropy
[0091] X ( s ) = Σ i log ( s i 2...
Embodiment 3
[0098] (1) Get the fabric image, such as Figure 8 shown.
[0099] (2) Use one-dimensional FFT to calculate the period of any row of grayscale data in the original image, and obtain the column basic period P 1 = 8 pixels.
[0100] (3) Use one-dimensional FFT to calculate the period of any column of grayscale data in the original image, and obtain the basic period P of the row 2 = 15 pixels.
[0101] (4) Implement Sobel operator horizontal filtering on the original image to obtain the filtered image as Figure 9 shown.
[0102] (5) Implement Sobel operator vertical filtering on the original image to obtain the filtered image as Figure 10 shown.
[0103] (6) According to Figure 9 and P 2 And combined with the formula for calculating the gray mean value
[0104] X ( s ) = 1 n Σ i = 1 ...
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