皮肤颜色检测算法实现

原理

在RGB颜色空间下满足：
R>95
AND G>40 B>20
AND MAX(R,G,B)-MIN(R,G,B)>15
AND ABS(R-G)>15
AND R>G
AND R>B
即可认为是皮肤颜色。

实现

#include 

//#define SKIN_DETECTION_DEBUG

#ifdef SKIN_DETECTION_DEBUG
#include 
#include 
#include 
#include 
#endif

int max(int a, int b, int c)
{
    int max = a;
    if(b > max)
        max = b;
    if(c > max)
        max = c;
    return max;
}

int min(int a, int b, int c)
{
    int min = a;
    if(b < min)
        min = b;
    if(c < min)
        min = c;
    return min;
}

/**
 * @brief skin_detection : exclude gray image
 * @param image
 * @param skin_ratio
 */
void skin_detection(const cv::Mat &image, double &skin_ratio)
{
    int rows = image.rows;
    int cols = image.cols;
    int skin_pix_num = 0;

#ifdef SKIN_DETECTION_DEBUG
    cv::Mat result = image.clone();
#endif

    for(int row = 0; row < rows; ++row)
    {
        for(int col = 0; col < cols; ++col)
        {
            int B = image.ptr(row)[col][0];
            int G = image.ptr(row)[col][1];
            int R = image.ptr(row)[col][2];
            if(R > 95 && G > 40 && B > 20
                    && R > G && R > B
                    && std::abs(R - G) > 15
                    && max(R, G, B) - min(R, G, B) > 15)
            {
                skin_pix_num++;

#ifdef SKIN_DETECTION_DEBUG
                result.ptr(row)[col][0] = 0;
                result.ptr(row)[col][1] = 0;
                result.ptr(row)[col][2] = 255;
#endif
            }
        }
    }

    skin_ratio = skin_pix_num * 1.0 / (rows * cols);

#ifdef SKIN_DETECTION_DEBUG
    char buffer[256];
    sprintf(buffer, "%5.5f", skin_ratio);
    std::string text = buffer;
    cv::putText(result, text, cv::Point(25, 25), cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(0,255,0), 1);
    cv::imshow("result", result);
#endif
}