opencv学习之路（30）、分水岭算法及图像修补

一、简介

二、分水岭算法

 #include "opencv2/opencv.hpp"

 using namespace cv;

 void main()

 {

     Mat srcImg = imread("E://bird.jpg");

     imshow("src", srcImg);

     Mat dstImg = srcImg.clone();

     //medianBlur(srcImg, srcImg, 5);

     //GaussianBlur(srcImg, srcImg, Size(5, 5), 0, 0);

     Mat imgMask(srcImg.size(), CV_8U, Scalar());//标记图像

     //标示背景图像

     rectangle(imgMask, Point(, ), Point(srcImg.cols - , srcImg.rows - ), Scalar(), );

     //标示鸟

     rectangle(imgMask, Point(srcImg.cols /  - , srcImg.rows /  - ), Point(srcImg.cols /  + , srcImg.rows /  + ), Scalar(), );

     //标示岩石

     rectangle(imgMask, Point(, ), Point(, ), Scalar(), );

     imshow("mask", imgMask);

     imgMask.convertTo(imgMask, CV_32S);

     watershed(srcImg, imgMask);  //调用分水岭算法

     Mat mark1, mark2;

     imgMask.convertTo(mark1, CV_8U);

     imshow("mark1", mark1);

     Mat mark3 = mark1.clone();

     bitwise_not(mark1, mark2);//图像取反

     imshow("mark2", mark2);

     threshold(mark1, mark1, , , CV_THRESH_TOZERO_INV);//CV_THRESH_TOZERO_INV:大于阈值都为0，其余正常        找出岩石

     threshold(mark2, mark2, , , CV_THRESH_TOZERO_INV);//因为取反后背景为0，所以筛选掉岩石后剩下的即为鸟

     threshold(mark3, mark3, , , CV_THRESH_BINARY);//鸟为128，大于128才能为255，所以找出了背景

     vector<vector<Point>> contours;

     vector<Vec4i> hierarcy;

     findContours(mark1, contours, hierarcy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);

     drawContours(dstImg, contours, -, Scalar(, , ), -, );

     vector<vector<Point>> contours2;

     vector<Vec4i> hierarcy2;

     findContours(mark2, contours2, hierarcy2, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);

     drawContours(dstImg, contours2, -, Scalar(, , ), -, );

     vector<vector<Point>> contours3;

     vector<Vec4i> hierarcy3;

     findContours(mark3, contours3, hierarcy3, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);

     drawContours(dstImg, contours3, -, Scalar(, , ), -, );

     Mat result = srcImg*0.5 + dstImg*0.5;

     imshow("result", result);

     waitKey();

 }

三、图像修补

#include "opencv2/opencv.hpp"

using namespace cv;

void main()

{

    Mat srcImg = imread("E://snow.jpg");

    Mat mask(srcImg.size(), CV_8U, Scalar());

    rectangle(mask, Point(, ), Point(, srcImg.rows), Scalar(), -, );

    Point org = Point(, );

    putText(srcImg, "OpenCV", org, CV_FONT_HERSHEY_SIMPLEX, 2.2f, CV_RGB(, , ), );

    imshow("src", srcImg);

    //putText( mask, "OpenCV", org, CV_FONT_HERSHEY_SIMPLEX, 2.2f, CV_RGB(255,255,255),2);

    rectangle(mask, Point(, ), Point(srcImg.cols, srcImg.rows), Scalar(), -, );

    imshow("mask", mask);

    Mat result;

    inpaint(srcImg, mask, result, , CV_INPAINT_NS); //图像修复

    imshow("result", result);

    waitKey();

}

四、祛痘

 #include "opencv2/opencv.hpp"

 using namespace cv;

 #define WINDOW_NAME0 "【原始图参考】"

 #define WINDOW_NAME1 "【原始图】"

 #define WINDOW_NAME2 "【修补后的效果图】"

 Mat srcImage0, srcImage1, inpaintMask;

 Point previousPoint(-, -);//原来的点坐标

 static void ShowHelpText()

 {

     printf("\n\n\t\t\t   当前使用的OpenCV版本为：" CV_VERSION);

     printf("\n\n  ----------------------------------------------------------------------------\n");

     printf("\n\t请在进行图像修复操作之前，在【原始图】窗口中进行适量的绘制"

         "\n\n\t按键操作说明: \n\n"

         "\t\t【鼠标左键】-在图像上绘制白色线条\n\n"

         "\t\t键盘按键【ESC】- 退出程序\n\n"

         "\t\t键盘按键【2】- 恢复原始图像\n\n"

         "\t\t键盘按键【1】或【SPACE】-进行图像修复操作 \n\n");

 }

 //-----------------------------------【On_Mouse( )函数】--------------------------------

 //          描述：响应鼠标消息的回调函数

 //----------------------------------------------------------------------------------------------

 static void On_Mouse(int event, int x, int y, int flags, void*)

 {

     //鼠标左键弹起消息

     if (event == CV_EVENT_LBUTTONUP || !(flags & CV_EVENT_FLAG_LBUTTON))//提取flags的CV_EVENT_FLAG_LBUTTON的标志位，！（）的意思是标志位无效，即鼠标左键不是拖拽动作

         previousPoint = Point(-, -);

     //鼠标左键按下消息

     else if (event == CV_EVENT_LBUTTONDOWN)

         previousPoint = Point(x, y);

     //鼠标按下并移动，进行绘制

     else if (event == CV_EVENT_MOUSEMOVE && (flags & CV_EVENT_FLAG_LBUTTON))

     {

         Point pt(x, y);

         if (previousPoint.x < )

             previousPoint = pt;

         //绘制白色线条

         line(inpaintMask, previousPoint, pt, Scalar::all(), , , );

         line(srcImage1, previousPoint, pt, Scalar::all(), , , );

         previousPoint = pt;

         imshow(WINDOW_NAME1, srcImage1);

     }

 }

 void main()

 {

     system("color 2F");

     ShowHelpText();

     //载入原始图并进行掩膜的初始化

     Mat srcImage = imread("face.jpg", -);

     if (!srcImage.data) { printf("读取图片错误，请确定目录下是否有imread函数指定图片存在~！ \n"); return; }

     srcImage0 = srcImage.clone();

     srcImage1 = srcImage.clone();

     inpaintMask = Mat::zeros(srcImage1.size(), CV_8U);

     imshow(WINDOW_NAME0, srcImage0);

     imshow(WINDOW_NAME1, srcImage1);

     //设置鼠标回调消息

     setMouseCallback(WINDOW_NAME1, On_Mouse, );

     //轮询按键，根据不同的按键进行处理

     while ()

     {

         //获取按键键值

         char c = (char)waitKey();

         //键值为ESC，程序退出

         if (c == )

             break;

         //键值为2，恢复成原始图像

         if (c == '')

         {

             inpaintMask = Scalar::all();

             srcImage.copyTo(srcImage1);

             imshow(WINDOW_NAME1, srcImage1);

         }

         //键值为1或者空格，进行图像修补操作

         if (c == '' || c == ' ')

         {

             Mat inpaintedImage;

             inpaint(srcImage1, inpaintMask, inpaintedImage, , CV_INPAINT_TELEA);

             imshow(WINDOW_NAME2, inpaintedImage);

         }

     }

 }