OpenCV之图像分割(五) 证件照背景替换

算法设计步骤：

代码

    #include "../common/common.hpp"

    void main(int argc, char** argv) 
    {
        Mat src = imread(getCVImagesPath("images/toux.jpg"));
        imshow("src5-13", src);

        // 组装数据
        int wid = src.cols;
        int hei = src.rows;
        int samplecount = wid*hei;
        int dims = src.channels();
        Mat points(samplecount, dims, CV_32F, Scalar(10)); // 行数为src的像素点数，列数为src的通道数，每列数据分别为src的b g r，src从上到下从左到右顺序读取数据
        int ind = 0;
        for (int row = 0; row < hei; row++)
        {
            for (int col = 0; col < wid; col++)
            {
                ind = row*wid + col; // points每列数据分别为src的b g r，src从上到下从左到右顺序读取数据
                Vec3b bgr = src.at<Vec3b>(row, col);
                points.at<float>(ind, 0) = static_cast<int>(bgr[0]);
                points.at<float>(ind, 1) = static_cast<int>(bgr[1]);
                points.at<float>(ind, 2) = static_cast<int>(bgr[2]);
            }
        }

        // 运行KMeans
        int numCluster = 4;
        Mat labels;
        Mat centers;
        TermCriteria criteria = TermCriteria(TermCriteria::EPS + TermCriteria::COUNT, 10, 0.1);
        kmeans(points, numCluster, labels, criteria, 3, KMEANS_PP_CENTERS, centers);

        // 去背景+遮罩生成
        Mat mask = Mat::zeros(src.size(), CV_8UC1); // 遮罩
        int index = src.rows * 2 + 2; // 不取边缘的左上点，往里靠2个位置
        int cindex = labels.at<int>(index, 0); // 证件照的左上或右上部分都是背景区域，取左上区域的分类index用作下面的对比改变背景色
        int height = src.rows;
        int width = src.cols;
        Mat dst; // 不做腐蚀和高斯模糊的效果图，人的轮廓周围会有一些杂点，所以需要腐蚀和高斯模糊取干扰
        src.copyTo(dst);
        for (int row = 0; row < height; row++) 
        {
            for (int col = 0; col < width; col++) 
            {
                index = row*width + col;
                int label = labels.at<int>(index, 0);
                if (label == cindex) {
                    dst.at<Vec3b>(row, col)[0] = 0; // dst
                    dst.at<Vec3b>(row, col)[1] = 0;
                    dst.at<Vec3b>(row, col)[2] = 0;
                    mask.at<uchar>(row, col) = 0; // 背景设为黑色
                }
                else { 
                    dst.at<Vec3b>(row, col) = src.at<Vec3b>(row, col);
                    mask.at<uchar>(row, col) = 255; // 人像部分设为白色，以便下面的腐蚀与高斯模糊操作
                }
            }
        }
        imshow("dst", dst);
        imshow("mask", mask);

        // 腐蚀 + 高斯模糊
        Mat k = getStructuringElement(MORPH_RECT, Size(3, 3), Point(-1, -1));
        erode(mask, mask, k);
        imshow("erode-mask", mask);
        GaussianBlur(mask, mask, Size(3, 3), 0, 0); // 腐蚀用的size是3，模糊的时候也要是3，效果才好
        imshow("Blur Mask", mask);

        // 通道混合
        RNG rng(12345);
        Vec3b color;
        color[0] = 217;// rng.uniform(0, 255);
        color[1] = 60;// rng.uniform(0, 255);
        color[2] = 160;// rng.uniform(0, 255);
        Mat result(src.size(), src.type());

        double w = 0.0;
        int b = 0, g = 0, r = 0;
        int b1 = 0, g1 = 0, r1 = 0;
        int b2 = 0, g2 = 0, r2 = 0;

        double time = getTickCount();
        for (int row = 0; row < height; row++) 
        {
            for (int col = 0; col < width; col++) 
            {
                int m = mask.at<uchar>(row, col);
                if (m == 255) {
                    result.at<Vec3b>(row, col) = src.at<Vec3b>(row, col); // 前景
                }
                else if (m == 0) {
                    result.at<Vec3b>(row, col) = color; // 背景
                }
                else { // 因为高斯模糊的关系，所以mask元素的颜色值除了黑白还有黑白边缘经过模糊后的非黑白值
                    w = m / 255.0; // bgr 1 与 bgr 2 的权重
                    b1 = src.at<Vec3b>(row, col)[0];
                    g1 = src.at<Vec3b>(row, col)[1];
                    r1 = src.at<Vec3b>(row, col)[2];

                    b2 = color[0];
                    g2 = color[1];
                    r2 = color[2];

                    b = b1*w + b2*(1.0 - w);
                    g = g1*w + g2*(1.0 - w);
                    r = r1*w + r2*(1.0 - w);

                    result.at<Vec3b>(row, col)[0] = b; // 最终边缘颜色值
                    result.at<Vec3b>(row, col)[1] = g;
                    result.at<Vec3b>(row, col)[2] = r;
                }
            }
        }
        cout << (getTickCount() - time) / getTickFrequency() << endl; // 0.0434462 ，比较耗时
        imshow("background replace", result);

        waitKey(0);
    }

效果图