matlab界面UI设计资料

一个实现图像灰度处理并归类于某已知相似图片的程序

软件：matlab2017a

算法：HU检索图像算法、Zernike算法

资料：

①：

matlab遍历文件夹下所有图片和遍历所有子文件夹下图片 - 专于技术，相信自我 - 博客园

https://www.cnblogs.com/tansuoxinweilai/p/9990191.html

②：

matlab设计gui文本框，怎么获取文本框输入的字符呢？_百度知道
https://zhidao.baidu.com/question/751372596254114212.html

③

ARMA Model Specifications - MATLAB & Simulink - MathWorks 中国
https://ww2.mathworks.cn/help/econ/arma-models.html?searchHighlight=arma&s_tid=doc_srchtitle

④：

MATLAB产生各种分布的随机数 - 百度文库
https://wenku.baidu.com/view/daa8cfeb02020740bf1e9b70.html

HU算法：用返回的七维向量作为一个图像的特征

 %**************************************************************************
 %图像检索——形状特征提取
 %利用HU的七个不变矩作为形状特征向量
 %Image : 输入图像数据
 %n: 返回七维形状特征行向量
 %**************************************************************************
 function n = Shape(Image)

  Image = imread('C:\Users\linuas\Desktop\test.jpg');
  [M,N,O] = size(Image);
 M = ;
 N = ;

 %--------------------------------------------------------------------------
 %彩色图像灰度化
 %--------------------------------------------------------------------------
 Gray = double(0.3*Image(:,:,)+0.59*Image(:,:,)+0.11*Image(:,:,));

 %--------------------------------------------------------------------------
 %用Canny边缘检测提取边缘保留边缘灰度图像
 %--------------------------------------------------------------------------
 % BW = uint8(edge(Gray,'canny'));
 Egray = uint8(edge(Gray,'canny'));
 for i = :M
     for j = :N
         if Egray(i,j)==
             Gray(i,j)=;
         end
     end
 end

 %--------------------------------------------------------------------------
 %Otsu提出的类判别分析法自动为每一幅廓图像选定阈值，然后用该阈值对图像二值化
 %--------------------------------------------------------------------------
 %计算灰度级归一化直方图
 for i = :
     h(i+) = size(find(Gray==i),);
 end
 p = h/sum(h);
 %计算灰度均值
 ut = ;
 for i = :
     ut = i*p(i+)+ut;
 end
 %计算直方图的零阶累积矩和一阶累积矩：
 for k = :
     w(k+) = sum(p(:k+));
     u(k+) = sum((:k).*p(:k+));
 end
 %计算类分离指标
 deltaB = zeros(,);
 for k = :
     if w(k+)~=&w(k+)~=
         deltaB(k+) = (ut*w(k+)-u(k+))^/(w(k+)*(-w(k+)));
     end
 end
 [value,thresh] = max(deltaB);
 % deltaB = zeros(,);
 % delta1 = zeros(,);
 % delta2 = zeros(,);
 % deltaW = zeros(,);
 % for k = :
 %     if w(k+)~=&w(k+)~=
 %         deltaB(k+) = (ut*w(k+)-u(k+))^/(w(k+)*(-w(k+)));
 %         delta1(k+) = ;
 %         delta2(k+) = ;
 %         for i = :k
 %             delta1(k+) = (i-u(k+)/w(k+))^*p(i+)+delta1(k+);
 %         end
 %         for i = k+:
 %             delta2(k+) = (i-(ut-u(k+))/(-w(k+)))^*p(k+)+delta2(k+);
 %         end
 %         deltaW(k+) = delta1(k+)+delta2(k+);
 %     end
 % end
 % for i = :
 %     if deltaB==
 %         yita=;
 %     else
 %         yita(i) = /(+deltaW(i)./deltaB(i));
 %     end
 % end
 % % D的最大值作为最佳阈值
 % [value,thresh] = max(yita);

 %对图像二值化
 for i = :M
     for j = :N
         if Gray(i,j)>=thresh
             BW(i,j) = ;
         else
             BW(i,j) = ;
         end
     end
 end

 %--------------------------------------------------------------------------
 %计算图像质心:(I,J)
 %--------------------------------------------------------------------------
 m00 = sum(sum(BW)); %零阶矩
 m01 = ;              %一阶矩
 m10 = ;              %一阶矩
 for i = :M
     for j = :N
         m01 = BW(i,j)*j+m01;
         m10 = BW(i,j)*i+m10;
     end
 end
 I = (m10)/(m00);
 J = m01/m00;

 %--------------------------------------------------------------------------
 %中心矩：
 %--------------------------------------------------------------------------
 u11 = ;
 u20 = ; u02 = ;
 u30 = ; u03 = ;
 u12 = ; u21 = ;
 for i = :M
     for j = :N
         u20 = BW(i,j)*(i-I)^+u20;
         u02 = BW(i,j)*(j-J)^+u02;
         u11 = BW(i,j)*(i-I)*(j-J)+u11;
         u30 = BW(i,j)*(i-I)^+u30;
         u03 = BW(i,j)*(j-J)^+u03;
         u12 = BW(i,j)*(i-I)*(j-J)^+u12;
         u21 = BW(i,j)*(i-I)^*(j-J)+u21;
     end
 end
 u20 = u20/m00^;
 u02 = u02/m00^;
 u11 = u11/m00^;
 u30 = u30/m00^(/);
 u03 = u03/m00^(/);
 u12 = u12/m00^(/);
 u21 = u21/m00^(/);
 %--------------------------------------------------------------------------
 %7个Hu不变矩：
 %--------------------------------------------------------------------------
 n() = u20+u02;
 n() = (u20-u02)^+*u11^;
 n() = (u30-*u12)^+(u03-*u21)^;
 n() = (u30+u12)^+(u03+u21)^;
 n() = (u30-*u12)*(u30+u12)*((u30+u12)^-*(u03+u21)^)+(u03-*u21)*(u03+u21)*((u03+u21)^-*(u30+u12)^);
 n() = (u20-u02)*((u30+u12)^-(u03+u21)^)+*u11*(u30+u12)*(u03+u21);
 n() = (*u21-u03)*(u30+u12)*((u30+u12)^-*(u03+u21)^)+(u30-*u12)*(u03+u21)*((u03+u21)^-*(u30+u12)^);% %--------------------------------------------------------------------------
 % %内部归一化：
 % %--------------------------------------------------------------------------
  en = mean(n);
  delta = sqrt(cov(n));
  n = abs(n-en)/(*delta);