(学习opencv二刷) 形态学算法处理

(学习opencv二刷) 形态学算法处理

1. 腐蚀，膨胀，开闭操作        

#include"stdafx.h"
#include <opencv2/opencv.hpp>    
#include <opencv2/imgproc/imgproc.hpp> 
using namespace std;
using namespace cv;
int main()
{Mat mSrc1 = imread("test1.jpg");resize(mSrc1, mSrc1, Size(512, 512));Mat mSrc2 = imread("test2.jpg");resize(mSrc2, mSrc2, Size(512, 512));Mat Diff;//= abs(mSrc1 - mSrc2);subtract(mSrc1, mSrc2, Diff);abs(Diff);imshow("Diff", Diff);waitKey(0);Mat erode_Diff;Mat element = getStructuringElement(MORPH_RECT, Size(3, 3), Point(0, 0));erode(Diff, erode_Diff, element);Mat clean_Diff;dilate(erode_Diff, clean_Diff, element);imshow("clean_Diff", clean_Diff);waitKey(0);/*Mat open_Diff;morphologyEx(Diff, open_Diff, MORPH_GRADIENT, element);imshow("open_Diff", open_Diff);waitKey(0);*/return 0;
}

原图：

运行结果：

2.图像降采样（缩小）

#include<iostream>
#include<opencv2/opencv.hpp>using namespace std;
using namespace cv;int main()
{Mat srcImage = imread("牛吃草.jpg");imshow("【原图】", srcImage);//其实就是缩小操作Mat dstImage;pyrDown(srcImage, dstImage, ls / 2, ws / 2));imshow("【处理后的图片】", dstImage);waitKey(0);return 0;
}

运行后的结果：

3.图像升采样（插值）

4.图像透视变换

设计思路：

1.图片预处理，利用霍夫变换检测出图片中长度超过10的直线
2.延长得到的直线
3.计算延长线的交点,找到四边形的四个边界点
4.利用得到的点拟合四边形
5.对得到的四边形的四个点排序
   5.1得到中心点
   5.2对得到的边界点排序
   5.3 透视变换

#include"stdafx.h"
#include <opencv2/imgproc/imgproc.hpp>  
#include <opencv2/highgui/highgui.hpp>  
#include <iostream> 
using namespace std;
using namespace cv;Point2f computeIntersect(cv::Vec4i a, cv::Vec4i b)
{int x1 = a[0], y1 = a[1], x2 = a[2], y2 = a[3], x3 = b[0], y3 = b[1], x4 = b[2], y4 = b[3];float denom;if (float d = ((float)(x1 - x2) * (y3 - y4)) - ((y1 - y2) * (x3 - x4))){cv::Point2f pt;pt.x = ((x1 * y2 - y1 * x2) * (x3 - x4) - (x1 - x2) * (x3 * y4 - y3 * x4)) / d;pt.y = ((x1 * y2 - y1 * x2) * (y3 - y4) - (y1 - y2) * (x3 * y4 - y3 * x4)) / d;return pt;}elsereturn cv::Point2f(-1, -1);
}
void OnDrawDotline(CvPoint s, CvPoint e, Mat workimg)
{CvPoint pa, pb;double k = (s.y - e.y) / (s.x - e.x + 0.000001);//不加0.000001 会变成曲线，斜率可能为0，即e.x-s.x可能为0    double h = ws;double w = ls;pa.x = w;pa.y = s.y + k*(w - s.x);line(workimg, e, pa, CV_RGB(255, 0, 255), 2, CV_AA, 0);   //向右画线    pb.y = e.y - k*e.x;pb.x = 0;line(workimg, pb, s, CV_RGB(255, 255, 0), 2, CV_AA, 0); //向左画线    }
void sortCorners(std::vector<cv::Point2f>& corners, cv::Point2f center)
{std::vector<cv::Point2f> top, bot;for (int i = 0; i < corners.size(); i++){if (corners[i].y < center.y)top.push_back(corners[i]);elsebot.push_back(corners[i]);}corners.clear();if (top.size() == 2 && bot.size() == 2) {cv::Point2f tl = top[0].x > top[1].x ? top[1] : top[0];cv::Point2f tr = top[0].x > top[1].x ? top[0] : top[1];cv::Point2f bl = bot[0].x > bot[1].x ? bot[1] : bot[0];cv::Point2f br = bot[0].x > bot[1].x ? bot[0] : bot[1];corners.push_back(tl);corners.push_back(tr);corners.push_back(br);corners.push_back(bl);}
}
int main()
{Mat mSrcImg;mSrcImg = imread("timg.jpg");if (pty())return -1;Mat pyTo(mSrcCopy);//1.预处理Mat mSrcCvt;cvtColor(mSrcImg, mSrcCvt,CV_BGR2GRAY);Mat mSrcBlur;blur(mSrcCvt, mSrcBlur, Size(3, 3));Mat mSrcCanny;Canny(mSrcBlur, mSrcCanny, 20, 200,3);vector<Vec4i>lines;HoughLinesP(mSrcCanny, lines, 1, CV_PI / 360, 70, 50, 20);Point2f pLeft, pRight;//2.延长每条线for (int i = 0; i < lines.size(); i++){pLeft = Point2f(lines[i][0], lines[i][1]);pRight = Point2f(lines[i][2], lines[i][3]);line(mSrcCopy, pLeft, pRight, Scalar(200, 0, 200), 2, 8);OnDrawDotline(pLeft, pRight, mSrcCopy);imshow("mSrcCopy", mSrcCopy); waitKey(0);}//3.计算延长线的交点,找到四边形的四个交点vector<Point2f> corners;for (int i = 0; i < lines.size(); i++){for (int j = i + 1; j < lines.size(); j++){Point2f pIntersection;pIntersection = computeIntersect(lines[i], lines[j]);if (pIntersection.x>0&& pIntersection.y>0&& pIntersection.x&ls&&pIntersection.y&ws){corners.push_back(pIntersection);circle(mSrcCopy, pIntersection, 8, Scalar(255, 0, 0), 2, 8);imshow("mSrcCopy", mSrcCopy); waitKey(0);}}}//C++: void approxPolyDP(InputArray curve, OutputArray approxCurve, double epsilon, bool closed)//参数详解;//InputArray curve : 一般是由图像的轮廓点组成的点集//	OutputArray approxCurve：表示输出的多边形点集//	double epsilon：主要表示输出的精度，就是另个轮廓点之间最大距离数，5, 6, 7，，8，，, , ，//	bool closed：表示输出的多边形是否封闭//4.拟合四边形vector<Point2f>approx;approxPolyDP(Mat(corners), approx, arcLength(Mat(corners), true)*0.02, true);if (approx.size()!=4){cout << "不是四边形！" << endl;return -1;}//5.对得到的四边形的四个点排序//5.1得到中心点Point2f center;for (int i = 0; i < corners.size(); i++)center += corners[i];center *= (1. / corners.size());circle(mSrcCopy, center, 5, Scalar(0, 0, 255), 2, 8);imshow("mSrcCopy", mSrcCopy); waitKey(0);sortCorners(corners, center);if (corners.size() == 0){cout << "The corners were not sorted correctly! "<<endl;return -1;}Mat quad = Mat(300, 200, CV_8UC3);vector<Point2f> quad_corns;quad_corns.push_back(Point2f(0, 0));quad_corns.push_back(ls, 0));quad_corns.push_back(ls, ws));quad_corns.push_back(Point2f(0, ws));Mat transmax = getPerspectiveTransform(corners, quad_corns);warpPerspective(mSrcImg,quad, transmax,quad.size());imshow("quad", quad); waitKey(0);return 0;
}

 原图：

运行结果：