Extracting texture feature source by gray-scale symbiosis matrix

Extracting texture feature source by gray-scale symbiosis matrix %************************************************************************** % image retrieval--texture features % based on Symbiosis matrix texture feature extraction, d=1,θ=0°,45°,90°,135° a total of four matrices % image grayscale level is 256 % reference "image retrieval based on color space and texture features" %function:t=texture (Image) %image: Input image data %T: Returns a eight-dimensional texture feature line vector %************************************************************************** function T = Vtex (Gray) Gray = Imread (' indentation. bmp '); M=size (gray,1); N=size (gray,2); %M = 256; %N = 256; %-------------------------------------------------------------------------- %1. converting each color component to grayscale %-------------------------------------------------------------------------- %gray = Double (0.3*image (:,:, 1) +0.59*image (:,:, 2) +0.11*image (:,:, 3)); %-------------------------------------------------------------------------- %2. To reduce the amount of computation, gray level compression of the original image, Gray quantization to 16 levels %-------------------------------------------------------------------------- For i = 1:m for j = 1:n For n = 1:256/16 if (n-1) *16<=gray (i,j) &&gray (i,j) <= (n-1) *16+15 Gray (i,j) = n-1; End End End End %-------------------------------------------------------------------------- %3. Calculate four symbiosis matrices P, take distance of 1, angle is 0,45,90,135 %-------------------------------------------------------------------------- P = zeros (16,16,4); for m = 1:16 For n = 1:16 For i = 1:m for j = 1:n If Gray (i,j) ==m-1 If J<n&&gray (i,j+1) ==n-1 P (m,n,1) = P (m,n,1) +1; End If I>1&&j<n&&gray (i-1,j+1) ==n-1 P (m,n,2) = P (m,n,2) +1; End If I<m&&gray (i+1,j) ==n-1 P (m,n,3) = P (m,n,3) +1; End If I<m&&j<n&&gray (i+1,j+1) ==n-1 P (m,n,4) = P (m,n,4) +1; End End End End P (n,m,1) = P (m,n,1); P (n,m,2) = P (m,n,2); P (n,m,3) = P (m,n,3); P (n,m,4) = P (m,n,4); If M==n P (m,n,:) = P (m,n,:)); End End End %%--------------------------------------------------------- % normalization of the symbiosis matrix %%--------------------------------------------------------- For n = 1:4 P (:,:, N) = P (:,:, N)/sum (SUM (P (:,:, N))); End %-------------------------------------------------------------------------- %4. Calculate energy, entropy, moment of inertia and related 4 texture parameters for symbiosis matrix %-------------------------------------------------------------------------- H = zeros (1,4); I = H; Ux = H; Uy = H; Deltax= H; DeltaY = H; C =h; For n = 1:4 E (n) = SUM (SUM (P (:,:, N). ^2)); Percent Energy For i = 1:16 for j = 1:16 If P (i,j,n) ~=0 H (n) =-P (i,j,n) *log (P (i,j,n)) +h (n); Percent entropy End I (n) = (i-j) ^2*p (i,j,n) +i (n); Percent Inertia moment Ux (n) = I*p (i,j,n) +ux (n); % Correlation in μx Uy (n) = J*p (i,j,n) +uy (n); % Correlation in Μy End End End For n = 1:4 For i = 1:16 for j = 1:16 DeltaX (n) = (I-ux (n)) ^2*p (i,j,n) +deltax (n); % correlation in σx due DeltaY (n) = (J-uy (n)) ^2*p (i,j,n) +deltay (n); % Correlation in Σy C (n) = I*j*p (i,j,n) +c (n); End End C (N) = (c (n)-ux (n) *uy (n))/deltax (n)/deltay (n); % dependency End %-------------------------------------------------------------------------- % energy, entropy, moment of inertia, correlation mean and standard deviation as final 8-dimensional texture characteristics %-------------------------------------------------------------------------- T (1) = mean (E); T (2) = sqrt (cov (E)); T (3) = mean (H); T (4) = sqrt (cov (H)); T (5) = mean (I); T (6) = sqrt (cov (I)); T (7) = mean (C); T (8) = sqrt (cov (C));

Extracting texture feature source by gray-scale symbiosis matrix