1.圖像二值化代碼：

A=imread('hw1.chips1.GIF'); %讀取到一張圖片

%thresh = graythresh(A); %自動確定二值化閾值

I2 = im2bw(A,120/255); %對圖像二值化

figure();

subplot(1,2,1);

imshow(A); %顯示二值化之前的圖片

title('原圖');

subplot(1,2,2);

imshow(I2); %顯示二值化之后的圖片

title('二值化');

2.求目標和背景均值和方差

oriImg = imread('hw1.chips1.GIF');

grayImg = oriImg;

%grayImg = rgb2gray(oriImg); %轉(zhuǎn)換為灰度圖

grayImg = double(grayImg);

[m, n] = size(oriImg);

foreCount = 0;

foreTotal = 0;

backCount = 0;

backTotal = 0;

for x = 1:m

for y = 1:n

if(grayImg(x,y) >= 128)

foreCount = foreCount + 1;

foreTotal = foreTotal + grayImg(x,y);

else

backCount = backCount + 1;

backTotal = backTotal + grayImg(x,y);

end

end

end

backMean = backTotal / backCount;

foreMean = foreTotal / foreCount;

backSqu = 0;

foreSqu = 0;

for x =1:m

for y = 1:n

if(grayImg(x,y) >= 128)

foreSqu = foreSqu + (grayImg(x,y) - foreMean)^2;

else

backSqu = backSqu + (grayImg(x,y) - backMean)^2;

end

end

end

backSqu = sqrt(backSqu / backTotal);

foreSqu = sqrt(foreSqu / foreTotal);

disp(strcat('背景均值', num2str(backMean)));

disp(strcat('背景標準差', num2str(backSqu)));

disp(strcat('前景均值', num2str(foreMean)));

disp(strcat('前景標準差', num2str(foreSqu)));

3.求目標和背景高斯分布(雙峰直方圖)

x = 0:0.1:256;

y1 = gaussmf(x,[backSqu^2 backMean]);

plot(x, y1);

hold on;

y2 = gaussmf(x,[foreSqu^2 foreMean]);

plot(x, y2);

title('高斯分布');

總結

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