license-plate-recognition.rar_SVM 字符识别_SVM字符识别_车牌字符分割_车牌检测 matla

close all clc I=imread('G:\项目\汽车牌照\code\version1\car7.jpg'); % figure(1),imshow(I);title('原图') I1=rgb2gray(I); % figure(2),subplot(1,2,1),imshow(I1);title('灰度图'); % figure(2),subplot(1,2,2),imhist(I1);title('灰度图直方图'); %% 图像预处理 %% 垂直边缘检测 得到I2 % I2=edge(I1,'roberts',0.15,'both'); % figure(3),subplot(2,2,1),imshow(I2);title('robert算子边缘检测') % I2=edge(I1,'prewitt',0.04); % figure(3),subplot(2,2,2),imshow(I2);title('prewitt算子边缘检测') I2=edge(I1,'canny',0.2); % figure(3),imshow(I2);title('canny算子边缘检测') %% 计算跳变点 %% HIS颜色判别 得到I3 I3=I2; I_size=size(I); for i=1:I_size(1) for j=1:I_size(2) if (I3(i,j)==1) Ihsi=I(i-1:i+1,j-1:j+1,:); flag=hsi_decision(2,2,Ihsi); if (flag<0.5) I3(i,j)=0; end end end end % figure(4),imshow(I3);title('his颜色判别') %% % 检测横向间距 % pj=1;k=0; % for i=1:10;for j=1:10;if (j<2)pj=1;end % if (I7(i,j)==1);k=k+1;s(k)=j-pj;pj=j;end % end;end % hist(s); I4=I3; %% 积分图像计算 用I4得到积分图像I5 s_line=zeros(I_size(1),I_size(2)); I5=s_line; s_line(1,1)=I4(1,1); I5(1,1)=I4(1,1); for i=2:I_size(1) %计算初始行 s_line(i,1)=I4(i,1); I5(i,1)=I5(i-1)+I4(i,1); end for i=2:I_size(2) I5(1,i)=I5(1,i-1)+I4(1,i); end for i=2:I_size(1) for j=2:I_size(2) s_line(i,j)=s_line(i,j-1)+I4(i,j); I5(i,j)=I5(i-1,j)+s_line(i,j); end end %% 矩形框窗口分析 loc=zeros(100,2); wlength=200;whigh=50; loc(1,1:2)=[-whigh/2,-wlength/2]; kwindow=1; for i=whigh/2:I_size(1)-whigh/2; for j=wlength:I_size(2)-wlength; winflag=0; if (I4(i,j)==1) for k=1:kwindow if (abs(j-loc(k,2))<wlength*2&&abs(i-loc(k,1))<whigh*2) winflag=1; break; end end if(winflag<1&&(I5(i+whigh/2,j+wlength/2)+I5(i-whigh/2,j-wlength/2)-I5(i+whigh/2,j-wlength/2)-I5(i-whigh/2,j+wlength/2))>200*50*0.05) kwindow=kwindow+1; loc(kwindow,1:2)=[i,j]; end end end end %% 利用水平投影求取车牌的高度 whigh=whigh*3; nIsize=[whigh+1,wlength+1]; horizonsum=zeros(nIsize(1),1); sumall=0; % for k=1:kwindow-1 k=1; Itemp=I3(loc(k+1,1)-0.4*whigh:loc(k+1,1)+0.6*whigh,loc(k+1,2)-0.48*wlength:loc(k+1,2)+0.52*wlength);%可删 figure(6);imshow(Itemp);%可删 for i=loc(k+1,1)-0.4*whigh:loc(k+1,1)+0.6*whigh for j=loc(k+1,2)-0.48*wlength:loc(k+1,2)+0.52*wlength if(I3(i,j)==1) horizonsum(i-loc(k+1,1)+0.4*whigh+1)=horizonsum(i-loc(k+1,1)+0.4*whigh+1)+1; sumall=sumall+1; end end end sumall=0.6*sumall/nIsize(1); for i=loc(k+1,1):-1:loc(k+1,1)-0.4*whigh if horizonsum(i-loc(k+1,1)+0.4*whigh+1)<sumall upsize=i; break; end end for i=loc(k+1,1):loc(k+1,1)+0.6*whigh if horizonsum(i-loc(k+1,1)+0.4*whigh+1)<sumall downsize=i; break; end end dd=downsize uu=upsize paihigh=ceil(downsize-upsize); pailength=ceil(paihigh*440/140); pailoch=floor(1/2*(downsize+upsize)); %边框与字的高度比为4:7 %% 车牌倾斜矫正 qingxiew=I2(ceil(pailoch-paihigh*7.5/7):ceil(pailoch+paihigh*7.5/7),ceil(loc(k+1,2)-pailength*0.55):ceil(loc(k+1,2)+0.65*pailength)); imshow(qingxiew); theta=65:115; % qingxiew 表示需要变换的图像，theta 表示变换的角度 % 返回值 r 表示的列中包含了对应于 theta中每一个角度的 Radon 变换结果 % 向量 xp 包含相应的沿 x轴的坐标 [r,xp]=radon(qingxiew,theta); %进行Radon变换 [maxr,rloc]=max(r(:)); %矩阵中的最大值坐标 [yr,xr]=ind2sub(size(r),rloc); %转化成二维坐标,x是点的横坐标，y是点的纵坐标 得到非零值从大到小的（x,y）坐标排序 angle=90-(xr+64); %旋转角度 I6=I(pailoch-ceil(paihigh*7.5/7):pailoch+ceil(paihigh*7.5/7),loc(k+1,2)-ceil(pailength*1):loc(k+1,2)+ceil(pailength*1),:); Itemp=I6; I6=imrotate(I6,angle); % 旋转图像 [m,n,l]=size(I6); I6_temp=I6((m+1)/2-ceil(paihigh*4.5/7):(m+1)/2+ceil(paihigh*4.5/7),(n+1)/2-pailength:(n+1)/2+pailength,:) I7=rgb2gray(I6_temp); I8=edge(I7,'canny',0.2); figure(8); imshow(I8); %显示校正后的图像 colorbar; %显示色彩条 title('校正后的图像'); [m,n]=size(I8); %% 车牌精确定位 输入I8 horizonsum=zeros(n,1); for i=1:m for j=1:n if(I8(i,j)==1) horizonsum(i)=horizonsum(i)+1; sumall=sumall+1; end end end sumall=0.6*sumall/m; for i=(m+1)/2:-1:1 if horizonsum(i)<sumall upsize=i+1;break; end end for i=(m+1)/2:m if horizonsum(i)<sumall downsize=i-1;break; end end I9=I6_temp(upsize:downsize,:,:); imshow(I9) b=rgb2gray(I9); imwrite(b,'1.车牌灰度图像.jpg'); figure(8);subplot(3,2,1),imshow(b),title('1.车牌灰度图像') g_max=double(max(max(b))); g_min=double(min(min(b))); T=round(g_max-(g_max-g_min)/3); % T 为二值化的阈值 [m,n]=size(b); d=(double(b)>=T); % d:二值图像 imwrite(d,'2.车牌二值图像.jpg'); figure(8);subplot(3,2,2),imshow(d),title('2.车牌二值图像') figure(8),subplot(3,2,3),imshow(d),title('3.均值滤波前') % 滤波 h=fspecial('average',3); d=im2bw(round(filter2(h,d))); imwrite(d,'4.均值滤波后.jpg'); figure(8),subplot(3,2,4),imshow(d),title('4.均值滤波后') % 某些图像进行操作 % 膨胀或腐蚀 % se=strel('square',3); % 使用一个3X3的正方形结果元素对象对创建的图像进行膨胀 % 'line'/'diamond'/'ball'... se=eye(2); % eye(n) returns the n-by-n identity matrix 单位矩阵 [m,n]=size(d); if bwarea(d)/m/n>=0.365 d=imerode(d,se); elseif bwarea(d)/m/n<=0.235 d=imdilate(d,se); end imwrite(d,'5.膨胀或腐蚀处理后.jpg'); figure(8),subplot(3,2,5),imshow(d),title('5.膨胀或腐蚀处理后') % end %% 寻找连续有文字的块，若长度大于某阈值，则认为该块有两个字符组成，需要分割 d=qiege(d); [m,n]=size(d); figure,subplot(2,1,1),imshow(d),title(n) k1=1;k2=1;s=sum(d);j=1; while j~=n while s(j)==0 j=j+1; end k1=j; while s(j)~=0 && j<=n-1 j=j+1; end k2=j-1; if k2-k1>=round(n/6.5) [val,num]=min(sum(d(:,[k1+5:k2-5]))); d(:,k1+num+5)=0; % 分割 end end % 再切割 d=qiege(d); % 切割出 7 个字符 y1=10;y2=0.25;flag=0;word1=[]; while flag==0 [m,n]=size(d); left=1;wide=0; while sum(d(:,wide+1))~=0 wide=wide+1; end if wide<y1 % 认为是左侧干扰 d(:,[1:wide])=0; d=qiege(d); else temp=qiege(imcrop(d,[1 1 wide m])); [m,n]=size(temp); all=sum(sum(temp)); two_thirds=sum(sum(temp([round(m/3):2*round(m/3)],:))); if two_thirds/all>y2 flag=1;word1=temp; % WORD 1 end d(:,[1:wide])=0;d=qiege(d); end end % 分割出第二个字符 [word2,d]=getword(d); % 分割出第三个字符 [word3,d]=getword(d); % 分割出第四个字符 [word4,d]=getword(d); % 分割出第五个字符 [word5,d]=getword(d); % 分割出第六个字符 [word6,d]=getword(d); % 分割出第七个字符 [word7,d]=getword(d); subplot(5,7,1),imshow(word1),title('1'); subplot(5,7,2),imshow(word2),title('2'); subplot(5,7,3),imshow(word3),title('3'); subplot(5,7,4),imshow(word4),title('4'); subplot(5,7,5),imshow(word5),title('5'); subplot(5,7,6),imshow(word6),title('6'); subplot(5,7,7),imshow(word7),title('7'); [m,n]=size(word1); % 商用系统程序中归一化大小为 40*20,此处演示 word1=imresize(word1,[40 20]); word2=imresize(word2,[40 20]); word3=imresize(word3,[40 20]); word4=imresize(word4,[40 20]); word5=imresize(word5,[40 20]); word6=imresize(word6,[40 20]); word7=imresize(word7,[40 20]); subplot(5,7,15),imshow(word1),title('1'); subplot(5,7,16),imshow(word2),title('2'); subplot(5,7,17),imshow(word3),title('3'); subplot(5,7,18),imshow(word4),title('4'); subplot(5,7,19),imshow(word5),title('5');