#include <opencv2/opencv.hpp> #include <iostream> using namespace std; using namespace cv; void ChangeImgBG(); Mat HandleImgData(Mat &img); /* 图片背景替换 知识点:分水岭分割、高斯模糊 处理步骤:数据组装-KMeans分割-背景消除-生成遮罩-模糊-输出 */ void ChangeImgBG() { const char* win1 = "window1"; const char* win2 = "window2"; const char* win3 = "window3"; const char* win4 = "window4"; const char* win5 = "window5"; const char* win6 = "window6"; namedWindow(win1, WINDOW_AUTOSIZE);//创建窗口 win1 namedWindow(win2, WINDOW_AUTOSIZE);//创建窗口 win2 namedWindow(win3, WINDOW_AUTOSIZE);//创建窗口 win3 namedWindow(win4, WINDOW_AUTOSIZE);//创建窗口 win4 namedWindow(win5, WINDOW_AUTOSIZE);//创建窗口 win5 namedWindow(win6, WINDOW_AUTOSIZE);//创建窗口 win6 Mat img1, img2; //加载图片 img1 = imread("pph.jpg"); if (img1.empty()) { cout << "image not found..." << endl; exit(0);//如果图片不存在,退出程序 } img2 = img1.clone(); //显示原始图片 imshow(win1, img1); //组装数据 Mat points = HandleImgData(img1); //Kmeans处理 int numCluster = 4; Mat labels; Mat centers; TermCriteria termCriteria = TermCriteria(TermCriteria::EPS + TermCriteria::COUNT, 10, 0.1); kmeans(points, numCluster, labels, termCriteria, 3, KMEANS_PP_CENTERS, centers); //遮罩 Mat mask = Mat::zeros(img1.size(), CV_8UC1); int index = img1.rows * 2 + 2; int cindex = labels.at<int>(index, 0);//背景设置为0 int height = img1.rows; int width = img1.cols; 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) { img2.at<Vec3b>(row, col)[0] = 0; img2.at<Vec3b>(row, col)[1] = 0; img2.at<Vec3b>(row, col)[2] = 0; mask.at<uchar>(row, col) = 0; } else { mask.at<uchar>(row, col) = 255; } } } //腐蚀 Mat k = getStructuringElement(MORPH_RECT, Size(3, 3), Point(-1, -1)); erode(mask, mask, k); imshow(win4, mask); //高斯模糊 GaussianBlur(mask, mask, Size(3, 3), 0, 0); imshow(win5, mask); //通道混合 RNG rng(12345); //背景颜色调整 Vec3b color; /*color[0] = rng.uniform(255, 255); color[1] = rng.uniform(255, 255); color[2] = rng.uniform(255, 255);*/ color[0] = 255; color[1] = 255; color[2] = 255; Mat result(img1.size(), img1.type()); double d1 = 0.0; int r = 0, g = 0, b = 0; int r1 = 0, g1 = 0, b1 = 0; int r2 = 0, g2 = 0, b2 = 0; 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) = img1.at<Vec3b>(row, col);//前景 } else if (m == 0) { result.at<Vec3b>(row, col) = color;//背景 } else { d1 = m / 255.0; b1 = img1.at<Vec3b>(row, col)[0]; g1 = img1.at<Vec3b>(row, col)[1]; r1 = img1.at<Vec3b>(row, col)[2]; b2 = color[0]; g2 = color[1]; r2 = color[2]; b = b1 * d1 + b2 * (1.0 - d1); g = g1 * d1 + g2 * (1.0 - d1); r = r1 * d1 + r2 * (1.0 - d1); result.at<Vec3b>(row, col)[0] = b; result.at<Vec3b>(row, col)[1] = g; result.at<Vec3b>(row, col)[2] = r; } } } //输出 imshow(win2, mask); imshow(win3, img2); imshow(win6, result); //保存处理后的图片 imwrite("pph_bg_white.jpg", result); } //组装样本数据 Mat HandleImgData(Mat &img) { int width = img.cols; int height = img.rows; int count1 = width * height; int channels1 = img.channels(); Mat points(count1, channels1, CV_32F, Scalar(10)); int index = 0; for (int row = 0; row < height; row++) { for (int col = 0; col < width; col++) { index = row * width + col; Vec3b bgr = img.at<Vec3b>(row, col); points.at<float>(index, 0) = static_cast<int>(bgr[0]); points.at<float>(index, 1) = static_cast<int>(bgr[1]); points.at<float>(index, 2) = static_cast<int>(bgr[2]); } } return points; } int main() { ChangeImgBG(); waitKey(0); return 0; }