%%
%編寫一個基於YCbCr色彩空間的膚色分割程序
%YCbCr是DVD、攝像機、數字電視等消費類視頻產品中常用的色彩編碼方案
%YCbCr在模擬分量視頻(analog component video)中也被常稱為YPbPr
%常見的3個基本色彩模型是RGB、CMYK、YUV
%YCbCr其中Y是指亮度分量，Cb指藍色色度分量，而Cr指紅色色度分量
%YCbCr與RGB的相互轉換 來自baidu
%Y=0.299R+0.587G+0.114B
%Cb=0.564(B-Y)
%Cr=0.713(R-Y)
%R=Y+1.402Cr
%G=Y-0.344Cb-0.714Cr
%B=Y+1.772Cb
%來自 wiki
%YPbPr (analog version of Y'CbCr) from R'G'B'
%Y' = Kr * R' + (1 - Kr - Kb) * G' + Kb * B'
%Pb = 0.5 * (B' - Y') / (1 - Kb)
%Pr = 0.5 * (R' - Y') / (1 - Kr)
....................................................
%R', G', B' in [0; 1]
%Y' in [0; 1]
%Pb in [-0.5; 0.5]
%Pr in [-0.5; 0.5]
%人臉檢測算法：
%1.精確定位人臉檢測候選區
%2.驗證已偵測人臉候選區的面部特征
%先要估算和糾正基於光補償技術的膚色模型，在進行色彩空間的非線性轉換
%空間轉換的橢圓膚色模型，參數式的橢圓就相當於假設的膚色高斯分布下的馬氏距離常數
%檢測到得膚色像素被反復的分割成局部顏色變化來連接基於這些部分的空間排列和類似他們顏色人臉候選區
%候選出來的大小能在13*13的像素和大約是輸入圖像大小的3/4之間變動。
%面部特征檢測模塊抑制了不包括任何面部特征
%Color Image --> Lighting Compensation --> Color Space Transformation
%--> Skin Color Detection --> Variance-based Segmentation -->
%Connected Component & Grouping --> Eye/Mouth Detection -->
%Face Boundary Detection --> Verifying/Weighting Eyes-Mouth Triangles
%%
%basic operation
clc;
clear all;
close all;
img = imread('2.jpg');
figure ;imshow(img);title('原始圖像');
[row col dim] = size(img);
img_double = double(img);
%get RGB channel
R = img_double(:,:,1);G = img_double(:,:,2);B = img_double(:,:,3);
figure ;
subplot(1,3,1);imshow(uint8(R));title('紅色分量');
subplot(1,3,2);imshow(uint8(G));title('綠色分量');
subplot(1,3,3);imshow(uint8(B));title('藍色分量');
%%
%convert RGB space to YcbCr-color space
R = double(R);G = double(G);B = double(B);
H =[65.4810 128.5530 24.9660;
-37.7970 -74.2030 112.0000;
112.0000 -93.7860 -18.2140];
% I = H/(sum(sum(H)));%按照常規進行矩陣的歸一化
I = H/255;%顏色像素空間的標准歸一化
Ymax = 235;Ymin = 16;
img_YCbCr(:,:,1) = I(1,1)*R+I(1,2)*G+I(1,3)*B+16;
img_YCbCr(:,:,2) = I(2,1)*R+I(2,2)*G+I(2,3)*B+128;
img_YCbCr(:,:,3) = I(3,1)*R+I(3,2)*G+I(3,3)*B+128;
if(img_YCbCr(:,:,1) > Ymax)
img_YCbCr(:,:,1) = Ymax;
elseif(img_YCbCr(:,:,1)<Ymin)
img_YCbCr(:,:,1)=Ymin;
end
if(img_YCbCr(:,:,2) > Ymax)
img_YCbCr(:,:,2) = Ymax;
elseif(img_YCbCr(:,:,2)<Ymin)
img_YCbCr(:,:,2)=Ymin;
end
if(img_YCbCr(:,:,3) > Ymax)
img_YCbCr(:,:,3) = Ymax;
elseif(img_YCbCr(:,:,3)<Ymin)
img_YCbCr(:,:,3)=Ymin;
end
%%
%在YCbCr色彩空間裡做膚色檢測，橢圓模型檢測Cb和Cr
y=img_YCbCr(:,:,1);
Cx = 109.38;Cy = 152.02;theta = 2.53;
ecx = 1.60;ecy = 2.41;a = 25.39;b = 14.03;
img_bin = zeros(row,col);
for i=1:row
for j=1:col
temp=cos(theta)*(img_YCbCr(i, j, 2) - Cx)+...
sin(theta)*(img_YCbCr(i, j, 3) - Cy);
y(i,j)=-sin(theta)*(img_YCbCr(i, j, 2) - Cx)+...
cos(theta)*(img_YCbCr(i, j, 3) - Cy);
lea = (temp - ecx).^2 / (a^2) + (y(i, j) - ecy).^2 / (b^2);
if(lea<=1) %將可能為膚色的點標記為白色
img_bin(i,j) = 255;
end
if(img_YCbCr(i,j,1) <= 80) %去除圖像中色彩很暗的點
img_bin(i,j) = 0;
end
end
end
%%
%show image
img_YCbCr = uint8(img_YCbCr);
figure ;imshow(img_YCbCr);title('YCBCR模型');
figure ;
subplot(1,3,1);imshow(img_YCbCr(:,:,1));title('Y分量');
subplot(1,3,2);imshow(img_YCbCr(:,:,2));title('CB分量');
subplot(1,3,3);imshow(img_YCbCr(:,:,3));title('CR分量');
figure ;imshow(img_bin);title('分割');
%用3*3模板對二值圖像進行膨脹操作
se = strel('diamond', 3);
img_bin = imdilate(img_bin, se);
figure ;
subplot(3,2,1);imshow(img_bin);title('diamond-膨脹');
se = strel('square', 3);
img_bin = imdilate(img_bin, se);
subplot(3,2,2);imshow(img_bin);title('square-膨脹');
se = strel('pair', [1,1]);
img_bin = imdilate(img_bin, se);
subplot(3,2,3);imshow(img_bin);title('pair-膨脹');
se = strel('disk', 3);
img_bin = imdilate(img_bin, se);
subplot(3,2,4);imshow(img_bin);title('disk-膨脹');
se = strel('rectangle', [1,3]);
img_bin = imdilate(img_bin, se);
subplot(3,2,5);imshow(img_bin);title('rectangle-膨脹');
se = strel('octagon', 3);
img_bin = imdilate(img_bin, se);
subplot(3,2,6);imshow(img_bin);title('octagon-膨脹');
