matlab界面UI设计资料

 %**************************************************************************

 %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);