模式识别实验报告

PAGEPAGE1模式识别实验报告基于BP神经网络的字符识别学院：信息与通信学院专业：信号与信息处理基于BP神经网络的字符识别1实验目的综合掌握模式识别的原理，了解识别过程的程序方法。2实验内容熟悉模式识别的理论方法，用选择一种合适的识别方法，对图像中的字符（英文字母）进行识别，能够区分出不同的形态的26个字母。3实验方法在Matlab中，采用BP神经网络，对读取的数据进行训练，进而识别。4程序设计4.1程序各图实验中主程序流程图如图4-1所示：图4-1主程序流程图其中图像预处理的流程如图4-2所示：图像输入灰度转化图像二值化图像分割归一化调整调整比例显示预处理结果图4-2图像预处理的流程神经网络训练的具体流程如图4-3所示：获取图像数据创建神经网络训练存储训练好的神经网络图4-3神经网络训练流程4.2程序清单%形成用户界面clearall;%添加图形窗口H=figure('Color',[0.850.850.85],...'position',[400300500400],...'Name','基于BP神经网络的英文字母识别',...'NumberTitle','off',...'MenuBar','none');%画坐标轴对象，显示原始图像h0=axes('position',[0.10.60.30.3]);%添加图像打开按钮h1=uicontrol(H,'Style','push',...'Position',[401008060],...'String','选择图片',...'FontSize',10,...'Call','op');%画坐标轴对象，显示经过预处理之后的图像h2=axes('position',[0.50.60.30.3]);%添加预处理按钮h3=uicontrol(H,'Style','push',...'Position',[1401008060],...'String','二值化',...'FontSize',10,...'Call','preprocess');%添加识别按钮h4=uicontrol(H,'Style','push',...'Position',[2401008060],...'String','字母识别',...'FontSize',10,...'Call','recognize');%添加显示识别结果的文本框%添加训练神经网络按钮h6=uicontrol(H,'Style','push',...'Position',[3401008060],...'String','网络训练',...'FontSize',10,...'Call','Example1Tr');%预处理%preprocessp1=ones(16,16);bw=im2bw(X,0.5);%转换成二值图像%用矩形框截取图像[i,j]=find(bw==0);imin=min(i);imax=max(i);jmin=min(j);jmax=max(j);bw1=bw(imin:imax,jmin:jmax);%调整比例，变换成16*16图像rate=16/max(size(bw1));bw1=imresize(bw1,rate);[i,j]=size(bw1);i1=round((16-i)/2);j1=round((16-j)/2);p1(i1+1:i1+i,j1+1:j1+j)=bw1;p1=-1.*p1+ones(16,16);%显示预处理的结果axes(h2);imshow(p1);%Example1Tr，训练网络M=1;%人数N=26*M;%样本数%获取26个大写字母图像的数据forkk=0:N-1p1=ones(16,16);%初始化16*16的二值图像（全白）m=strcat(int2str(kk),'.bmp');%形成文件名x=imread(m,'bmp');%读取图像bw=im2bw(x,0.5);%转换成二值图像数据%用矩形框截取[i,j]=find(bw==0);%查找像素为黑的坐标%取边界坐标imin=min(i);imax=max(i);jmin=min(j);jmax=max(j);bw1=bw(imin:imax,jmin:jmax);%截取%调整比例，缩放成16*16的图像rate=16/max(size(bw1));bw1=imresize(bw1,rate);%会存在转换误差%将bw1转换成的16*16图像p1[i,j]=size(bw1);i1=round((16-i)/2);j1=round((16-j)/2);p1(i1+1:i1+i,j1+1:j1+j)=bw1;p1=-1.*p1+ones(16,16);%将p1转换成输入向量form=0:15p(m*16+1:(m+1)*16,kk+1)=p1(1:16,m+1);endend%形成目标向量forkk=0:M-1forii=0:25t(kk+ii+1)=ii;endend%设置输入向量范围pr(1:256,1)=0;pr(1:256,2)=1;%创建两层BP神经网络，隐层有25个节点net=newff(pr,[251],{'logsig''purelin'},'traingdx','learngdm');net.trainParam.epochs=2500;net.trainParam.goal=0.001;net.trainParam.show=10;net.trainParam.lr=0.05;%训练神经网络net=train(net,p,t);%存储训练好的神经网络%recognize，字符识别%生成向量形式M=figure('Color',[0.750.750.75],...'position',[200200400200],...'Name','基于BP神经网络的英文字母识别结果',...'NumberTitle','off',...'MenuBar','none');M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','请先训练网络',...'FontSize',12,...'call','delete(M(1))');form=0:15q(m*16+1:(m+1)*16,1)=p1(1:16,m+1);end%识别[a,Pf,Af]=sim(net,q);a=round(a);switchacase0,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是A',...'FontSize',12,...'call',...'delete(M(1))');case1,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是B',...'FontSize',12,...'call',...'delete(M(1))');case2,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是C',...'FontSize',12,...'call',...'delete(M(1))');case3,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是D',...'FontSize',12,...'call',...'delete(M(1))');case4,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是E',...'FontSize',12,...'call',...'delete(M(1))');case5,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是F',...'FontSize',12,...'call',...'delete(M(1))');case6,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是G',...'FontSize',12,...'call',...'delete(M(1))');case7,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是H',...'FontSize',12,...'call',...'delete(M(1))');case8,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是I',...'FontSize',12,...'call',...'delete(M(1))');case9,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是J',...'FontSize',12,...'call',...'delete(M(1))');case10,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是K',...'FontSize',12,...'call',...'delete(M(1))');case11,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是L',...'FontSize',12,...'call',...'delete(M(1))');case12,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是M',...'FontSize',12,...'call',...'delete(M(1))');case13,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是N',...'FontSize',12,...'call',...'delete(M(1))');case14,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是O',...'FontSize',12,...'call',...'delete(M(1))');case15,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是P',...'FontSize',12,...'call',...'delete(M(1))');case16,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是Q',...'FontSize',12,...'call',...'delete(M(1))');case17,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是R',...'FontSize',12,...'call',...'delete(M(1))');case18,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是S',...'FontSize',12,...'call',...'delete(M(1))');case19,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是T',...'FontSize',12,...'call',...'delete(M(1))');case20,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是U',...'FontSize',12,...'call',...'delete(M(1))');case21,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是V',...'FontSize',12,...'call',...'delete(M(1))');case22,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是W',...'FontSize',12,...'call',...'delete(M(1))');case23,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是X',...'FontSize',12,...'call',...'delete(M(1))');case24,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是Y',...'FontSize',12,...'call',...'delete(M(1))');case25,M0=uicontrol(M,'Style','push',...'Position',[1508013040],...'String','这个字母是Z',...'FontSize',12,...'call',...'delete(M(1))');End%op%读取图像文件[filename,pathname]=uigetfile({'*.bmp';'*.jpg';...'*.gif';'*.*'},...'PickanImageFile');X=imread([pathname,filename]);%显示图像axes(h0);%将h0设置为当前坐标轴句柄imshow(X);%在h0上显示原始图像5实验结果图5-1为实验的主窗口，用于选择图片，进行二值化，网络训练和字符识别。运行程序后，将弹出次窗口，选择图片后，先进行二值化处理，然后在进行网络训练，最后字符识别。图5-1主窗口图5-2网络训练图5-3字符识别结果