《visual c++matlab图像处理与识别实用案例精选》源码

				I=imread('brand02.jpg');
				HS_I=double(I);
				tic
				G=gradient(HS_I);  % 计算梯度值
				[y,x]=size(I);
				T=60;
				%%%%%%% 商标文字分割 %%%%%%%%%%
				n=30;
				GY=zeros(y,1);                 
				for j=1:y   
				    for i=1:x-n
				         Max=max(G(j,i:i+n));
				         Min=min(G(j,i:i+n));
				         MGD(j,i)=Max-Min;       % 计算最大梯度差
				         if (MGD(j,i)>T)         
				             GY(j,1)=GY(j,1)+1;  % MGD大于阈值的次数统计
				         end    
				    end
				end    
				[temp MaxY]=max(GY);
				PY1=MaxY;
				while ((GY(PY1,1)>=n)&&(PY1>1))  % 次数阈值检测
				       PY1=PY1-1;
				end    
				PY2=MaxY;
				while ((GY(PY2,1)>=n)&&(PY2				       PY2=PY2+1;
				end
				%%%%%%%%%% X 方向的分割 %%%%%%%%%%%
				n=15;
				GX=zeros(1,x);
				for i=1:x
				    for j=1:y-n
				         Max=max(G(j:j+n,i));
				         Min=min(G(j:j+n,i));
				         MGD(j,i)=Max-Min;
				         if (MGD(j,i)>T)
				             GX(1,i)=GX(1,i)+1;
				         end
				     end
				 end
				 PX1=1;
				while (((GX(1,PX1)				       PX1=PX1+1;
				end    
				PX2=x;
				while (((GX(1,PX2)				       PX2=PX2-1;
				end    
				
				HS_I=uint8(HS_I);
				IY=HS_I(PY1:PY2,PX1:PX2);
				t=toc
				%%%%%%%%%%%%%%%%%%%%%%%%%%
				figure,imshow(HS_I);
				figure,plot(MGD(40,:));grid
				figure,plot(MGD(140,:));grid
				figure,imshow(IY);