区域分割（OpenCV）
区域分割
区域生长
分裂合并
水域分割
Hough变换
Hough变换原理
广义Hough变换
#include <opencv2/highgui.hpp> #include <opencv2/imgproc.hpp> #include <iostream> using namespace std; using namespace cv; Mat g_srcImage, g_dstImage, g_midImage;//原始图、中间图和效果图 vector<Vec4i> g_lines;//定义一个矢量结构g_lines用于存放得到的线段矢量集合 //变量接收的TrackBar位置参数 int g_nthreshold = 100; static void on_HoughLines(int, void*);//回调函数 static void ShowHelpText(); int main() { ShowHelpText(); Mat g_srcImage = imread("1.jpg"); //工程目录下应该有一张名为1.jpg的素材图 imshow("【原始图】", g_srcImage); namedWindow("【效果图】", 1); createTrackbar("值", "【效果图】", &g_nthreshold, 200, on_HoughLines); Canny(g_srcImage, g_midImage, 50, 200, 3);//进行一次canny边缘检测 cvtColor(g_midImage, g_dstImage, COLOR_GRAY2BGR);//转化边缘检测后的图为灰度图 on_HoughLines(g_nthreshold, 0); HoughLinesP(g_midImage, g_lines, 1, CV_PI / 180, 80, 50, 10); imshow("【效果图】", g_dstImage); waitKey(0); return 0; } static void on_HoughLines(int, void*) { Mat dstImage = g_dstImage.clone(); Mat midImage = g_midImage.clone(); vector<Vec4i> mylines; HoughLinesP(midImage, mylines, 1, CV_PI / 180, g_nthreshold + 1, 50, 10); for (size_t i = 0; i < mylines.size(); i++) { Vec4i l = mylines[i]; line(dstImage, Point(l[0], l[1]), Point(l[2], l[3]), Scalar(23, 180, 55), 1, LINE_AA); } imshow("【效果图】", dstImage); } static void ShowHelpText() { printf("当前使用的OpenCV版本为：" CV_VERSION); printf("\n请调整滚动条观察图像效果！"); }
#include "opencv2/highgui/highgui.hpp" #include "opencv2/imgproc/imgproc.hpp" #include <iostream> using namespace std; using namespace cv; #define WINDOW_NAME "【程序窗口】" //为窗口标题定义的宏 Mat g_srcImage, g_dstImage; Mat g_map_x, g_map_y; int update_map(int key); static void ShowHelpText();//输出帮助文字 int main(int argc, char** argv) { ShowHelpText(); g_srcImage = imread("1.jpg", 1); if (!g_srcImage.data) { printf("读取图片错误，请确定目录下是否有imread函数指定的图片存在~！ \n"); return false; } imshow("原始图", g_srcImage); g_dstImage.create(g_srcImage.size(), g_srcImage.type()); g_map_x.create(g_srcImage.size(), CV_32FC1); g_map_y.create(g_srcImage.size(), CV_32FC1); namedWindow(WINDOW_NAME, WINDOW_AUTOSIZE); imshow(WINDOW_NAME, g_srcImage); while (1) { //获取键盘按键 int key = waitKey(0); //判断ESC是否按下，若按下便退出 if ((key & 255) == 27) { cout << "程序退出...........\n"; break; } //根据按下的键盘按键来更新 map_x & map_y的值. 然后调用remap( )进行重映射 update_map(key); //此句代码的OpenCV2版为： //remap( g_srcImage, g_dstImage, g_map_x, g_map_y, CV_INTER_LINEAR, BORDER_CONSTANT, Scalar(0,0, 0) ); //此句代码的OpenCV3版为： remap(g_srcImage, g_dstImage, g_map_x, g_map_y, INTER_LINEAR, BORDER_CONSTANT, Scalar(0, 0, 0)); //显示效果图 imshow(WINDOW_NAME, g_dstImage); } return 0; } int update_map(int key) { //双层循环，遍历每一个像素点 for (int j = 0; j < g_srcImage.rows; j++) { for (int i = 0; i < g_srcImage.cols; i++) { switch (key) { case '1': // 键盘【1】键按下，进行第一种重映射操作 if (i > g_srcImage.cols * 0.25 && i < g_srcImage.cols * 0.75 && j > g_srcImage.rows * 0.25 && j < g_srcImage.rows * 0.75) { g_map_x.at<float>(j, i) = static_cast<float>(2 * (i - g_srcImage.cols * 0.25) + 0.5); g_map_y.at<float>(j, i) = static_cast<float>(2 * (j - g_srcImage.rows * 0.25) + 0.5); } else { g_map_x.at<float>(j, i) = 0; g_map_y.at<float>(j, i) = 0; } break; case '2':// 键盘【2】键按下，进行第二种重映射操作 g_map_x.at<float>(j, i) = static_cast<float>(i); g_map_y.at<float>(j, i) = static_cast<float>(g_srcImage.rows - j); break; case '3':// 键盘【3】键按下，进行第三种重映射操作 g_map_x.at<float>(j, i) = static_cast<float>(g_srcImage.cols - i); g_map_y.at<float>(j, i) = static_cast<float>(j); break; case '4':// 键盘【4】键按下，进行第四种重映射操作 g_map_x.at<float>(j, i) = static_cast<float>(g_srcImage.cols - i); g_map_y.at<float>(j, i) = static_cast<float>(g_srcImage.rows - j); break; } } } return 1; } static void ShowHelpText() { printf("当前使用的OpenCV版本为：" CV_VERSION); printf("\n欢迎来到重映射示例程序："); printf("\n按键操作说明: \n" "键盘按键【ESC】- 退出程序\n" "键盘按键【1】- 第一种映射方式\n" "键盘按键【2】- 第二种映射方式\n" "键盘按键【3】- 第三种映射方式\n" "键盘按键【4】- 第四种映射方式\n"); }
#include <opencv2/highgui.hpp> #include <opencv2/imgproc.hpp> #include <iostream> using namespace cv; using namespace std; #define WINDOW_NAME1 "【原始图窗口】" //为窗口标题定义的宏 #define WINDOW_NAME2 "【经过Warp后的图像】" //为窗口标题定义的宏 #define WINDOW_NAME3 "【经过Warp和Rotate后的图像】" //为窗口标题定义的宏 static void ShowHelpText(); int main() { ShowHelpText(); //定义两组点，代表两个三角形 Point2f srcTriangle[3]; Point2f dstTriangle[3]; //定义一些Mat变量 Mat rotMat(2, 3, CV_32FC1); Mat warpMat(2, 3, CV_32FC1); Mat srcImage, dstImage_warp, dstImage_warp_rotate; srcImage = imread("1.jpg", 1); if (!srcImage.data) { printf("读取图片错误，请确定目录下是否有imread函数指定的图片存在~！ \n"); return false; } // 设置目标图像的大小和类型与源图像一致 dstImage_warp = Mat::zeros(srcImage.rows, srcImage.cols, srcImage.type()); srcTriangle[0] = Point2f(0, 0); srcTriangle[1] = Point2f(static_cast<float>(srcImage.cols - 1), 0); srcTriangle[2] = Point2f(0, static_cast<float>(srcImage.rows - 1)); dstTriangle[0] = Point2f(static_cast<float>(srcImage.cols * 0.0), static_cast<float>(srcImage.rows * 0.33)); dstTriangle[1] = Point2f(static_cast<float>(srcImage.cols * 0.65), static_cast<float>(srcImage.rows * 0.35)); dstTriangle[2] = Point2f(static_cast<float>(srcImage.cols * 0.15), static_cast<float>(srcImage.rows * 0.6)); warpMat = getAffineTransform(srcTriangle, dstTriangle); warpAffine(srcImage, dstImage_warp, warpMat, dstImage_warp.size()); // 计算绕图像中点顺时针旋转50度缩放因子为0.6的旋转矩阵 Point center = Point(dstImage_warp.cols / 2, dstImage_warp.rows / 2); double angle = -50.0; double scale = 0.6; rotMat = getRotationMatrix2D(center, angle, scale); warpAffine(dstImage_warp, dstImage_warp_rotate, rotMat, dstImage_warp.size()); imshow(WINDOW_NAME1, srcImage); imshow(WINDOW_NAME2, dstImage_warp); imshow(WINDOW_NAME3, dstImage_warp_rotate); waitKey(0); return 0; } static void ShowHelpText() { printf("当前使用的OpenCV版本为：" CV_VERSION); printf("\n欢迎来到仿射变换综合示例程序！"); }
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