Charged insulator string icing bridging degree intelligent image analysis method
An intelligent image and analysis method technology, applied in the field of image analysis, can solve the problem of effective information loss and other issues
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[0101] Example: Set 16*16 non-overlapping windows, calculate the gray level co-occurrence matrix in the four directions of 0°, 45°, 90°, and 135° in the window, so that it satisfies:
[0102] p(i,j,d,0°)=#{(x 1 ,y 1 )(x 2 ,y 2 )∈Nx ×N y |f(x 1 ,y 1 )=i, f(x 2 ,y 2 ) = j;
[0103] x 2 -x 1 =0,|y 2 -y 1 |=d}
[0104] p(i,j,d,45°)=#{(x 1 ,y 1 )(x 2 ,y 2 )∈N x ×N y |f(x 1 ,y 1 )=i, f(x 2 ,y 2 ) = j;
[0105] x 2 -x 1 =-d,y 2 -y 1 = d or x 2 -x 1 =d,y 2 -y 1 =-d}
[0106] p(i,j,d,90°)=#{(x 1 ,y 1 )(x 2 ,y 2 )∈N x ×N y |f(x 1 ,y 1 )=i, f(x 2 ,y 2 ) = j;
[0107] |x 2 -x 1 |=d,y 2 -y 1 =0}
[0108] p(i,j,d,135°)=#{(x 1 ,y 1 )(x 2 ,y 2 )∈N x ×N y |f(x 1 ,y 1 )=i, f(x 2 ,y 2 ) = j;
[0109] x 2 -x 1 =d,y 2 -y 1 = d or x 2 -x 1 =-d,y 2 -y 1 =-d}
[0110] Among them, the symbol #{x} represents the number of elements satisfying the set condition.
[0111] Typical eigenvalues of the gray level co-occurrence matrix, incl...
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