RGB颜色空间肤色检测

RGB颜色空间肤色检测

1.算法原理

       基于RGB颜色空间的简单阈值肤色识别

       在human skin color clustering for face detection一文中提出如下简单的判别算式：

　　　　　　R>95 And G>40 And B>20 And R>G And R>B And Max(R,G,B)-Min(R,G,B)>15 And Abs(R-G)>15 

　　  算法非常之简单，同样主要把复杂的判断条件放到后面去判断，能有效的降低程序的执行时间。

2.参考代码：

int DetectFace(IMAGE_TYPE *bmp_img,DWORD width,DWORD height)
{
DWORD i,j,bfsize,Source_linebyte,lineByte,SourceSpeed,dstSpeed;
T_U8 *dst_img,*img_data,*Source_img;
int R,G,B,Max,Min;
int colorTablesize;
int newbiBitCount =8;
RGBQUAD colortable[256];
RGBQUAD *pColorTable1 = colortable;

BITMAPFILEHEADER bf;
BITMAPINFOHEADER bi;

FILE *DetectFace_fp = fopen("DetectFace.bmp","wb");

if(NULL == DetectFace)
{
printf("Can't open Fragment.bmp\n");
return -1;
}

memset(&bf, 0, sizeof(bf));
memset(&bi, 0, sizeof(bi));

bf.bfType = (WORD)0x4d42;

//8位图像数据每行字节数为4的倍数
lineByte = (width * newbiBitCount / 8 + 3) / 4 * 4;
colorTablesize = 1024;
bf.bfSize = sizeof(BITMAPFILEHEADER)+sizeof(BITMAPINFOHEADER)+colorTablesize+lineByte*height;//图像数据加上调色板信息和前两部分BMP文件信息
bf.bfReserved1 = 0;
bf.bfReserved2 = 0;
bf.bfOffbits = sizeof(BITMAPFILEHEADER)+sizeof(BITMAPINFOHEADER)+colorTablesize;//注意此offset是BMP前三部分数据，也就是真正图像数据的前面几部分之和

bi.biSize   = 40;
bi.biHeight = height;
bi.biWidth  = width;
bi.biPlanes = 1;
bi.biCompression = 0;
bi.biBitCount = newbiBitCount;//每一个像素由8 bits表示
bi.biSizeImage = lineByte*height;
bi.biXPelsPerMeter = 0;
bi.biYPelsPerMter = 0;
bi.biClrImportant = 0;
bi.biClrUsed = 0;
Source_linebyte = WIDTHBYTES(width*24);
Source_img = bmp_img+54;

for (i = 0; i<256; ++i)
{
colortable[i].rgbBlue = i;
colortable[i].rgbGreen = i;
colortable[i].rgbRed = i;
colortable[i].rgbReserved = 0;
}

fwrite(&bf,sizeof(BITMAPFILEHEADER),1,DetectFace_fp);
fwrite(&bi,sizeof(BITMAPINFOHEADER),1,DetectFace_fp);
fwrite(pColorTable1, sizeof(RGBQUAD), 256, DetectFace_fp);
img_data = bmp_img+54;

dst_img = (T_U8*)malloc(height*lineByte);
memset(dst_img,0,height*lineByte);

for(i = 0;i < height;i++)
{
SourceSpeed = Source_linebyte*i;
dstSpeed = lineByte*i;
for(j = 0;j < width;j++)
{
B = img_data[SourceSpeed];
G = img_data[SourceSpeed+1];
R = img_data[SourceSpeed+2];

if(R > 95 && G > 40 && B > 20 && R > B && R > G && abs(R - G) > 15)
{
if (B >= G)
{
Max = B;
Min = G;
}
else
{
Max = G;
Min = B;
}
if (R > Max)
Max = R;
else if (R < Min)
Min = R;
if (Max - Min > 15) dst_img[dstSpeed] = 255;
}
dstSpeed++;
SourceSpeed += 3;
}
}

fwrite(dst_img,lineByte*height,1,DetectFace_fp);
fclose(DetectFace_fp);
DetectFace_fp = NULL;
free(dst_img);
return 0;

}

3.算法结果

有很多误判的区域，还是不够准确！

参考文献：

肤色检测算法 - 基于不同颜色空间简单区域划分的皮肤检测算法