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1、用Prewitt算子檢測圖像的邊緣

I = imread('bacteria.BMP');

BW1 = edge(I,'prewitt',0.04);?????????????% 0.04為梯度閾值

figure(1);

imshow(I);

figure(2);

imshow(BW1);

2、用不同σ值的LoG算子檢測圖像的邊緣

I = imread('bacteria.BMP');

BW1 = edge(I,'log',0.003); % σ=2

imshow(BW1);title('σ=2')

BW1 = edge(I,'log',0.003,3); % σ=3

figure, imshow(BW1);title('σ=3')

3、用Canny算子檢測圖像的邊緣

I = imread('bacteria.BMP');

imshow(I);

BW1 = edge(I,'canny',0.2);

figure,imshow(BW1);

4、圖像的閾值分割

I=imread('blood1.tif');

imhist(I);??????????% 觀察灰度直方圖， 灰度140處有谷，確定閾值T=140

I1=im2bw(I,140/255); % im2bw函數(shù)需要將灰度值轉(zhuǎn)換到[0,1]范圍內(nèi)

figure,imshow(I1);

5、用水線閾值法分割圖像

afm = imread('afmsurf.tif');figure, imshow(afm);

se = strel('disk', 15);

Itop = imtophat(afm, se); % 高帽變換

Ibot = imbothat(afm, se); % 低帽變換

figure, imshow(Itop, []);???% 高帽變換，體現(xiàn)原始圖像的灰度峰值

figure, imshow(Ibot, []);???% 低帽變換，體現(xiàn)原始圖像的灰度谷值

Ienhance = imsubtract(imadd(Itop, afm), Ibot);% 高帽圖像與低帽圖像相減，增強圖像

figure, imshow(Ienhance);

Iec = imcomplement(Ienhance); % 進一步增強圖像

Iemin = imextendedmin(Iec, 20); figure,imshow(Iemin) % 搜索Iec中的谷值

Iimpose = imimposemin(Iec, Iemin);

wat = watershed(Iimpose); % 分水嶺分割

rgb = label2rgb(wat); figure, imshow(rgb); % 用不同的顏色表示分割出的不同區(qū)域

6、對矩陣進行四叉樹分解

I = [ 1?????1?????1?????1?????2?????3?????6?????6

?????????1?????1?????2?????1?????4?????5?????6?????8

?????????1?????1?????1?????1????10????15?????7?????7

?????????1?????1?????1?????1????20????25?????7?????7

????????20????22????20????22?????1?????2?????3?????4

????????20????22????22????20?????5?????6?????7?????8

????????20????22????20????20?????9????10????11????12

????????22????22????20????20????13????14????15????16];

S = qtdecomp(I,5);

full(S)

7、將圖像分為文字和非文字的兩個類別

I=imread('4-11.jpg');

I1=I(:,:,1);

I2=I(:,:,2);

I3=I(:,:,3);

[y,x,z]=size(I);

d1=zeros(y,x);

d2=d1;

myI=double(I);

I0=zeros(y,x);

for i=1:x

????for j=1:y

%歐式聚類

d1(j,i)=sqrt((myI(j,i,1)-180)^2+(myI(j,i,2)-180)^2+(myI(j,i,3)-180)^2);

d2(j,i)=sqrt((myI(j,i,1)-200)^2+(myI(j,i,2)-200)^2+(myI(j,i,3)-200)^2);

???????

????????if (d1(j,i)>=d2(j,i))

?????????????I0(j,i)=1;

????????end

????end

end

figure(1);

imshow(I);

% 顯示RGB空間的灰度直方圖，確定兩個聚類中心(180,180,180)和(200,200,200)

figure(2);????

subplot(1,3,1);

imhist(I1);

subplot(1,3,2);

imhist(I2);

subplot(1,3,3);

imhist(I3);

figure(4);

imshow(I0);

8、形態(tài)學梯度檢測二值圖像的邊緣

I=imread('wrod213.bmp');

imshow(I);

I=~I;????????% 腐蝕運算對灰度值為1的進行

figure, imshow(I);

SE=strel('square',3); % 定義3×3腐蝕結(jié)構(gòu)元素

J=imerode(~I,SE);

BW=(~I)-J;????????% 檢測邊緣

figure,imshow(BW);

9、形態(tài)學實例——從PCB圖像中刪除所有電流線，僅保留芯片對象

I=imread('circbw.tif');

imshow(I);

SE=strel('rectangle',[40 30]); % 結(jié)構(gòu)定義

J=imopen(I,SE);????????????% 開啟運算

figure,imshow(J);

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