【纹理特征提取】基于matlab局部二值模式LBP图像纹理特征提取【含Matlab源码 1931期】.zip

function lbphist = lbphistogram(img) % 将彩色图像转换为灰度图像 if size(img,3) == 3 img = rgb2gray(img); end % 计算图像尺寸 [m,n] = size(img); % lbp初始化,最外1圈不计算 lbp = uint8(zeros(m-1,n-1)); % 从(2,2)开始统计LBP for i=2:m-1 for j=2:n-1 % 存储8位二进制值 b = uint8(zeros(1,8)); % 周围8领域分别与中心像素最比较，得到每一位的值 if(img(i-1,j-1)>img(i,j)) b(:,1) = 1; end if(img(i-1,j)>img(i,j)) b(:,2) = 1; end if(img(i-1,j+1)>img(i,j)) b(:,3) = 1; end if(img(i,j+1)>img(i,j)) b(:,4) = 1; end if(img(i+1,j+1)>img(i,j)) b(:,5) = 1; end if(img(i+1,j)>img(i,j)) b(:,6) = 1; end if(img(i+1,j-1)>img(i,j)) b(:,7) = 1; end if(img(i,j-1)>img(i,j)) b(:,8) = 1; end % 逆时针排列，最高为权值最低 bins = b(:,8)*2^0 + b(:,7)*2^1 + b(:,6)*2^2 + b(:,5)*2^3 + ... b(:,4)*2^4 + b(:,3)*2^5 + b(:,2)*2^6 + b(:,1)*2^7; % 目标像素的LBP值 lbp(i-1,j-1)=bins; end end [counts,~] = imhist(lbp); lbphist = counts; % normalize lbphist = lbphist/sum(lbphist); % lbphist = mapminmax(lbphist', 0, 1)';