matlab圖像分割算法源碼.doc
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matlab 圖像分割算法源碼1.圖像反轉(zhuǎn)MATLAB程序?qū)崿F(xiàn)如下:I=imread(xian.bmp);J=double(I);J=-J+(256-1); %圖像反轉(zhuǎn)線性變換H=uint8(J);subplot(1,2,1),imshow(I);subplot(1,2,2),imshow(H);2.灰度線性變換MATLAB程序?qū)崿F(xiàn)如下:I=imread(xian.bmp);subplot(2,2,1),imshow(I);title(原始圖像);axis(50,250,50,200);axis on; %顯示坐標(biāo)系I1=rgb2gray(I);subplot(2,2,2),imshow(I1);title(灰度圖像);axis(50,250,50,200);axis on; %顯示坐標(biāo)系J=imadjust(I1,0.1 0.5,); %局部拉伸,把0.1 0.5內(nèi)的灰度拉伸為0 1subplot(2,2,3),imshow(J);title(線性變換圖像0.1 0.5);axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系K=imadjust(I1,0.3 0.7,); %局部拉伸,把0.3 0.7內(nèi)的灰度拉伸為0 1subplot(2,2,4),imshow(K);title(線性變換圖像0.3 0.7);axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系3.非線性變換MATLAB程序?qū)崿F(xiàn)如下:I=imread(xian.bmp);I1=rgb2gray(I);subplot(1,2,1),imshow(I1);title(灰度圖像);axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系J=double(I1);J=40*(log(J+1);H=uint8(J);subplot(1,2,2),imshow(H);title(對(duì)數(shù)變換圖像);axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系4.直方圖均衡化MATLAB程序?qū)崿F(xiàn)如下:I=imread(xian.bmp);I=rgb2gray(I);figure;subplot(2,2,1);imshow(I);subplot(2,2,2);imhist(I);I1=histeq(I);figure;subplot(2,2,1);imshow(I1);subplot(2,2,2);imhist(I1);5.線性平滑濾波器用MATLAB實(shí)現(xiàn)領(lǐng)域平均法抑制噪聲程序:I=imread(xian.bmp);subplot(231)imshow(I)title(原始圖像)I=rgb2gray(I);I1=imnoise(I,salt & pepper,0.02);subplot(232)imshow(I1)title(添加椒鹽噪聲的圖像)k1=filter2(fspecial(average,3),I1)/255; %進(jìn)行3*3模板平滑濾波k2=filter2(fspecial(average,5),I1)/255; %進(jìn)行5*5模板平滑濾波k3=filter2(fspecial(average,7),I1)/255; %進(jìn)行7*7模板平滑濾波k4=filter2(fspecial(average,9),I1)/255; %進(jìn)行9*9模板平滑濾波subplot(233),imshow(k1);title(3*3模板平滑濾波);subplot(234),imshow(k2);title(5*5模板平滑濾波);subplot(235),imshow(k3);title(7*7模板平滑濾波);subplot(236),imshow(k4);title(9*9模板平滑濾波);6.中值濾波器用MATLAB實(shí)現(xiàn)中值濾波程序如下:I=imread(xian.bmp);I=rgb2gray(I);J=imnoise(I,salt&pepper,0.02);subplot(231),imshow(I);title(原圖像);subplot(232),imshow(J);title(添加椒鹽噪聲圖像);k1=medfilt2(J); %進(jìn)行3*3模板中值濾波k2=medfilt2(J,5,5); %進(jìn)行5*5模板中值濾波k3=medfilt2(J,7,7); %進(jìn)行7*7模板中值濾波k4=medfilt2(J,9,9); %進(jìn)行9*9模板中值濾波subplot(233),imshow(k1);title(3*3模板中值濾波);subplot(234),imshow(k2);title(5*5模板中值濾波);subplot(235),imshow(k3);title(7*7模板中值濾波);subplot(236),imshow(k4);title(9*9模板中值濾波);7.用Sobel算子和拉普拉斯對(duì)圖像銳化:I=imread(xian.bmp);subplot(2,2,1),imshow(I);title(原始圖像);axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系I1=im2bw(I);subplot(2,2,2),imshow(I1);title(二值圖像);axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系H=fspecial(sobel); %選擇sobel算子J=filter2(H,I1); %卷積運(yùn)算subplot(2,2,3),imshow(J);title(sobel算子銳化圖像);axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系h=0 1 0,1 -4 1,0 1 0; %拉普拉斯算子J1=conv2(I1,h,same); %卷積運(yùn)算subplot(2,2,4),imshow(J1);title(拉普拉斯算子銳化圖像);axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系8.梯度算子檢測(cè)邊緣用MATLAB實(shí)現(xiàn)如下:I=imread(xian.bmp);subplot(2,3,1);imshow(I);title(原始圖像);axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系I1=im2bw(I);subplot(2,3,2);imshow(I1);title(二值圖像);axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系I2=edge(I1,roberts);figure;subplot(2,3,3);imshow(I2);title(roberts算子分割結(jié)果);axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系I3=edge(I1,sobel);subplot(2,3,4);imshow(I3);title(sobel算子分割結(jié)果);axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系I4=edge(I1,Prewitt);subplot(2,3,5);imshow(I4);title(Prewitt算子分割結(jié)果);axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系9.LOG算子檢測(cè)邊緣用MATLAB程序?qū)崿F(xiàn)如下:I=imread(xian.bmp);subplot(2,2,1);imshow(I);title(原始圖像);I1=rgb2gray(I);subplot(2,2,2);imshow(I1);title(灰度圖像);I2=edge(I1,log);subplot(2,2,3);imshow(I2);title(log算子分割結(jié)果);10.Canny算子檢測(cè)邊緣用MATLAB程序?qū)崿F(xiàn)如下:I=imread(xian.bmp);subplot(2,2,1);imshow(I);title(原始圖像)I1=rgb2gray(I);subplot(2,2,2);imshow(I1);title(灰度圖像);I2=edge(I1,canny);subplot(2,2,3);imshow(I2);title(canny算子分割結(jié)果);11.邊界跟蹤(bwtraceboundary函數(shù))clcclear allI=imread(xian.bmp);figureimshow(I);title(原始圖像);I1=rgb2gray(I); %將彩色圖像轉(zhuǎn)化灰度圖像threshold=graythresh(I1); %計(jì)算將灰度圖像轉(zhuǎn)化為二值圖像所需的門(mén)限BW=im2bw(I1, threshold); %將灰度圖像轉(zhuǎn)化為二值圖像figureimshow(BW);title(二值圖像);dim=size(BW);col=round(dim(2)/2)-90; %計(jì)算起始點(diǎn)列坐標(biāo)row=find(BW(:,col),1); %計(jì)算起始點(diǎn)行坐標(biāo)connectivity=8;num_points=180;contour=bwtraceboundary(BW,row,col,N,connectivity,num_points);%提取邊界figureimshow(I1);hold on;plot(contour(:,2),contour(:,1), g,LineWidth ,2);title(邊界跟蹤圖像);12.Hough變換I= imread(xian.bmp);rotI=rgb2gray(I);subplot(2,2,1);imshow(rotI);title(灰度圖像);axis(50,250,50,200);grid on;axis on;BW=edge(rotI,prewitt);subplot(2,2,2);imshow(BW);title(prewitt算子邊緣檢測(cè)后圖像);axis(50,250,50,200);grid on;axis on;H,T,R=hough(BW);subplot(2,2,3);imshow(H,XData,T,YData,R,InitialMagnification,fit);title(霍夫變換圖);xlabel(theta),ylabel(rho);axis on , axis normal, hold on;P=houghpeaks(H,5,threshold,ceil(0.3*max(H(:);x=T(P(:,2);y=R(P(:,1);plot(x,y,s,color,white);lines=houghlines(BW,T,R,P,FillGap,5,MinLength,7);subplot(2,2,4);,imshow(rotI);title(霍夫變換圖像檢測(cè));axis(50,250,50,200);grid on;axis on;hold on;max_len=0;for k=1:length(lines)xy=lines(k).point1;lines(k).point2;plot(xy(:,1),xy(:,2),LineWidth,2,Color,green);plot(xy(1,1),xy(1,2),x,LineWidth,2,Color,yellow);plot(xy(2,1),xy(2,2),x,LineWidth,2,Color,red);len=norm(lines(k).point1-lines(k).point2);if(lenmax_len)max_len=len;xy_long=xy;endendplot(xy_long(:,1),xy_long(:,2),LineWidth,2,Color,cyan);13.直方圖閾值法用MATLAB實(shí)現(xiàn)直方圖閾值法:I=imread(xian.bmp);I1=rgb2gray(I);figure;subplot(2,2,1);imshow(I1);title(灰度圖像)axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系m,n=size(I1); %測(cè)量圖像尺寸參數(shù)GP=zeros(1,256); %預(yù)創(chuàng)建存放灰度出現(xiàn)概率的向量for k=0:255 GP(k+1)=length(find(I1=k)/(m*n); %計(jì)算每級(jí)灰度出現(xiàn)的概率,將其存入GP中相應(yīng)位置endsubplot(2,2,2),bar(0:255,GP,g) %繪制直方圖title(灰度直方圖)xlabel(灰度值)ylabel(出現(xiàn)概率)I2=im2bw(I,150/255);subplot(2,2,3),imshow(I2);title(閾值150的分割圖像)axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系I3=im2bw(I,200/255); %subplot(2,2,4),imshow(I3);title(閾值200的分割圖像)axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系14. 自動(dòng)閾值法:Otsu法用MATLAB實(shí)現(xiàn)Otsu算法:clcclear allI=imread(xian.bmp);subplot(1,2,1),imshow(I);title(原始圖像)axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系level=graythresh(I); %確定灰度閾值BW=im2bw(I,level);subplot(1,2,2),imshow(BW);title(Otsu法閾值分割圖像)axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系15.膨脹操作I=imread(xian.bmp); %載入圖像I1=rgb2gray(I);subplot(1,2,1);imshow(I1);title(灰度圖像)axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系se=strel(disk,1); %生成圓形結(jié)構(gòu)元素I2=imdilate(I1,se); %用生成的結(jié)構(gòu)元素對(duì)圖像進(jìn)行膨脹subplot(1,2,2);imshow(I2);title(膨脹后圖像);axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系16.腐蝕操作MATLAB實(shí)現(xiàn)腐蝕操作I=imread(xian.bmp); %載入圖像I1=rgb2gray(I);subplot(1,2,1);imshow(I1);title(灰度圖像)axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系se=strel(disk,1); %生成圓形結(jié)構(gòu)元素I2=imerode(I1,se); %用生成的結(jié)構(gòu)元素對(duì)圖像進(jìn)行腐蝕subplot(1,2,2);imshow(I2);title(腐蝕后圖像);axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系17.開(kāi)啟和閉合操作用MATLAB實(shí)現(xiàn)開(kāi)啟和閉合操作I=imread(xian.bmp); %載入圖像subplot(2,2,1),imshow(I);title(原始圖像);axis(50,250,50,200);axis on; %顯示坐標(biāo)系I1=rgb2gray(I);subplot(2,2,2),imshow(I1);title(灰度圖像);axis(50,250,50,200);axis on; %顯示坐標(biāo)系se=strel(disk,1); %采用半徑為1的圓作為結(jié)構(gòu)元素I2=imopen(I1,se); %開(kāi)啟操作I3=imclose(I1,se); %閉合操作subplot(2,2,3),imshow(I2);title(開(kāi)啟運(yùn)算后圖像);axis(50,250,50,200);axis on; %顯示坐標(biāo)系subplot(2,2,4),imshow(I3);title(閉合運(yùn)算后圖像);axis(50,250,50,200);axis on; %顯示坐標(biāo)系18.開(kāi)啟和閉合組合操作I=imread(xian.bmp); %載入圖像subplot(3,2,1),imshow(I);title(原始圖像);axis(50,250,50,200);axis on; %顯示坐標(biāo)系I1=rgb2gray(I);subplot(3,2,2),imshow(I1);title(灰度圖像);axis(50,250,50,200);axis on; %顯示坐標(biāo)系se=strel(disk,1);I2=imopen(I1,se); %開(kāi)啟操作I3=imclose(I1,se); %閉合操作subplot(3,2,3),imshow(I2);title(開(kāi)啟運(yùn)算后圖像);axis(50,250,50,200);axis on; %顯示坐標(biāo)系subplot(3,2,4),imshow(I3);title(閉合運(yùn)算后圖像);axis(50,250,50,200);axis on; %顯示坐標(biāo)系se=strel(disk,1);I4=imopen(I1,se);I5=imclose(I4,se);subplot(3,2,5),imshow(I5); %開(kāi)閉運(yùn)算圖像title(開(kāi)閉運(yùn)算圖像);axis(50,250,50,200);axis on; %顯示坐標(biāo)系I6=imclose(I1,se);I7=imopen(I6,se);subplot(3,2,6),imshow(I7); %閉開(kāi)運(yùn)算圖像title(閉開(kāi)運(yùn)算圖像);axis(50,250,50,200);axis on; %顯示坐標(biāo)系19.形態(tài)學(xué)邊界提取利用MATLAB實(shí)現(xiàn)如下:I=imread(xian.bmp); %載入圖像subplot(1,3,1),imshow(I);title(原始圖像);axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系I1=im2bw(I);subplot(1,3,2),imshow(I1);title(二值化圖像);axis(50,250,50,200);grid on; %顯示網(wǎng)格線axis on; %顯示坐標(biāo)系I2=bwperim(I1); %獲取區(qū)域的周長(zhǎng)subplot(1,3,3),imshow(I2);title(邊界周長(zhǎng)的二值圖像);axis(50,250,50,200);grid on;axis on;20.形態(tài)學(xué)骨架提取利用MATLAB實(shí)現(xiàn)如下:I=imread(xian.bmp);subplot(2,2,1),imshow(I);title(原始圖像);axis(50,250,50,200);axis on;I1=im2bw(I);subplot(2,2,2),imshow(I1);title(二值圖像);axis(50,250,50,200);axis on;I2=bwmorph(I1,skel,1);subplot(2,2,3),imshow(I2);title(1次骨架提取);axis(50,250,50,200);axis on;I3=bwmorph(I1,skel,2);subplot(2,2,4),imshow(I3);title(2次骨架提取);axis(50,250,50,200);axis on;21.直接提取四個(gè)頂點(diǎn)坐標(biāo)I = imread(xian.bmp);I = I(:,:,1);BW=im2bw(I);figureimshow(BW)x,y=getpts- 1.請(qǐng)仔細(xì)閱讀文檔,確保文檔完整性,對(duì)于不預(yù)覽、不比對(duì)內(nèi)容而直接下載帶來(lái)的問(wèn)題本站不予受理。
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