Matlab车型识别系统[Matlab面板版].zip

clc;%清空变量 mainfc; c=imread('streetcar1.jpg');%车子图片 streetcar=c;%赋值 b=imread('street.jpg');%街景,背景图 figure(1); subplot(231); imshow(c);%显示原图 title('原图'); subplot(232); c=imsubtract(c,b);%相减 imshow(c); title('作差图'); %将待识别图像与背景图像进行比较，识别出车子，并只留下车子 for i=1:600 %从第1到600行 for j=1:800 %从1-800列 if (abs(double(b(i,j,1))-double(streetcar(i,j,1)))>2) %b(i,j,1)表示H通道 ,b(i,j,2)表示 S通道,b(i,j,3)表示V通道 c(i,j,1)=0;%每个通道 的 像素相同,那么变为黑色,否则 为白色 c(i,j,2)=0; c(i,j,3)=0; elseif (abs(double(b(i,j,2))-double(streetcar(i,j,2)))>2) c(i,j,1)=0; c(i,j,2)=0; c(i,j,3)=0; elseif (abs(double(b(i,j,3))-double(streetcar(i,j,3)))>2) c(i,j,1)=0; c(i,j,2)=0; c(i,j,3)=0; else c(i,j,1)=255; c(i,j,2)=255; c(i,j,3)=255; end end end %图像处理，包括灰度化，二值化和腐蚀，去除噪声 %c=imcomplement(c) %c=immultiply(a,c); c=rgb2gray(c);%c是 经过上述 hsv通道处理作差后的彩色图象 leftcar=dither(c); subplot(233); imshow(leftcar); title('车子轮廓初步定位'); leftcar=~leftcar;%取反 subplot(234); imshow(leftcar); title('反色处理'); leftcar=bwmorph(leftcar,'erode',1); leftcar=~leftcar; %leftcar=bwmorph(leftcar,'erode',5); leftcar=~leftcar; vsumleftcar=sum(leftcar,2); %找到车棚，并得到宽度 for i=1:599 if (vsumleftcar(i)<80) & (vsumleftcar(i+1)>80) top=i; break; end end for i=1:599 if (vsumleftcar(600-i)<80) & (vsumleftcar(599-i)>80) bottom=600-i; break; end end topvalue=vsumleftcar(bottom-ceil((bottom-top)*4/5)); bottomvalue=vsumleftcar(bottom-ceil((bottom-top)*2/5)); maxvalue=max(vsumleftcar); percent=topvalue/maxvalue; subplot(235); imshow(~leftcar); title('车子轮廓'); h=findobj(gcf,'Tag','text2'); %根据判断依据确定车型 if (percent>=0.2) & (percent<=0.5) str1=sprintf('小汽车\n\n'); str2=num2str(percent); string=[str1 '高宽比:' str2]; msgbox(string,'温馨提示','none'); return end