opencv基本图像处理

1.反转图像函数：cv::flip()void flip(InputArray src, OutputArray dst, int flipCode);  参数fipCode: 整数，水平发转；0垂直反转；负数，水平垂直均反转。2.sobel边缘检测函数：cv::sobel()例程：//从文件中读入图像  const char* imagename = "lena.BMP";  Mat img = imread(imagename);  if(img.empty()) //如果读入图像失败  {      fprintf(stderr, "Can not load image %s\n", imagename);      return -1;  }    namedWindow("original image");  imshow("original image",img);      //Mat result;  //flip(img, result, -1);    //反转图像  Mat sobelX, sobelY, sobel;  Sobel(img, sobelX, CV_16S, 1, 0);  Sobel(img, sobelY, CV_16S, 0, 1);  sobel = abs(sobelX) + abs(sobelY);    //搜索sobel极大值  double sobmin, sobmax;  minMaxLoc(sobel, &sobmin, &sobmax);    //变换为8位图像  //sobelImage = -alpha*sobel + 255  Mat sobelImage;  sobel.convertTo(sobelImage, CV_8U, -255./sobmax, 255);    namedWindow("sobelImage");  imshow("sobelImage", sobelImage);    Mat sobelThresholded;  double threadVal = 200;   threshold(sobelImage, sobelThresholded, threadVal, 255, THRESH_BINARY);    namedWindow("sobelThresholded");  imshow("sobelThresholded", sobelThresholded);  3. 读取单通道灰度图像Mat img = imread("lena.bmp", 0);  imshow("lena", img);  建立的img是单通道的。4. 中值滤波CvImgProc cvImgProc;    Mat img = imread("lena.bmp", 0); //读取图像  namedWindow("lena", CV_WINDOW_AUTOSIZE);  imshow("lena", img);    Mat saltImg = img.clone(); //复制图像  cvImgProc.salt(saltImg, 1000); //添加椒盐噪声  namedWindow("saltlena", CV_WINDOW_AUTOSIZE);  imshow("saltlena", saltImg);    Mat blurImg;  medianBlur(saltImg, blurImg, 3); //5*5中值滤波  namedWindow("blurImg", CV_WINDOW_AUTOSIZE);  imshow("blurImg", blurImg);  5. canny边缘检测Mat img = imread("lena.bmp", 0); //读取图像  namedWindow("lena", CV_WINDOW_AUTOSIZE);  imshow("lena", img);    Mat contours;  Canny(img, contours, 125, 350); //canny边缘检测  namedWindow("contours", CV_WINDOW_AUTOSIZE);  imshow("contours", contours);    Mat contoursInv;   threshold(contours, contoursInv, 128, 255, THRESH_BINARY_INV); //反转边缘图像  namedWindow("contoursInv", CV_WINDOW_AUTOSIZE);  imshow("contoursInv", contoursInv);  6. 腐蚀操作原理：腐蚀替换当前像素位像素集合中找到的最小像素值。//读取输入图像  Mat image = imread("binary.bmp");  namedWindow("binary");  imshow("binary", image);    //腐蚀图像  Mat eroded; //目标图像   //使用默认的方形结构元素(等价于以下注释掉的代码)  erode(image, eroded, Mat());  //Mat element(3, 3, CV_8U, Scalar(1));  //erode(image, eroded, element);  //显示腐蚀后的图像  namedWindow("Eroded Image");  imshow("Eroded Image", eroded);  7. 膨胀操作原理：膨胀是替换当前像素位像素集合中找到的最大像素值。//读取输入图像  Mat image = imread("binary.bmp");  namedWindow("binary");  imshow("binary", image);    //膨胀图像  Mat dilated; //目标图像  //使用默认的方形结构元素(等价于以下注释掉的代码)  dilate(image, dilated, Mat());  //Mat element(3, 3, CV_8U, Scalar(1));  //dilate(image, dilated, element);  //显示膨胀后的图像  namedWindow("Dilated Image");  imshow("Dilated Image", dilated);  还可以进行多次膨胀，只需将执行函数该为：dilate(image, dilated, Mat(), Point(-1, -1), 3);  8. 图像二值化CvImgProc cvImgProc;    //读取输入图像  //Mat image = imread("lena.bmp");  IplImage* iplImage = cvLoadImage("lena.bmp");    IplImage* iplImage2 = cvCreateImage(cvSize(512, 512), IPL_DEPTH_8U, 1);     double thresholdVal = cvImgProc.cvThresholdOtsu(iplImage);  printf("thresholdVal = %lf", thresholdVal);    Mat image(iplImage, false);  Mat image3;  threshold(image, image3, thresholdVal, 255, THRESH_BINARY);  namedWindow("binary");  imshow("binary", image3);  得出阈值是127version 2:CvImgProc cvImgProc;    //读取输入图像  Mat image = imread("camera.tiff");    Mat image2;  int thresholdVal = cvImgProc.cvOtsu(image);  printf("thresholdVal = %d", thresholdVal);  threshold(image, image2, thresholdVal, 255, THRESH_BINARY);  namedWindow("binary");  imshow("binary", image2);  imwrite("cameraBinary.bmp", image2);  9.闭运算//读取输入图像  Mat image = imread("lenaBinary.bmp");  Mat element5(3, 3, CV_8U, Scalar(1));  Mat closed;  morphologyEx(image, closed, MORPH_CLOSE, element5);  namedWindow("closed");  imshow("closed", closed);  10.开运算//读取输入图像  Mat image = imread("lenaBinary.bmp");  Mat element3(3, 3, CV_8U, Scalar(1));  Mat opened;  morphologyEx(image, opened, MORPH_CLOSE, element3);  namedWindow("closed");  imshow("closed", opened);  11.三通道彩色图像转单通道灰度图像//读取输入图像  Mat image = imread("pepper.bmp");  namedWindow("image");  imshow("image", image);  Mat image2;  cvtColor(image, image2, CV_BGR2GRAY, 1); //尾参：无/0保留通道个数；1单通道；3三通道。  namedWindow("image2");  imshow("image2", image2);  imwrite("pepperGray.bmp", image2);  12.求图像的最大值和最小值//读取输入图像  Mat image = imread("lena.bmp");  namedWindow("image");  imshow("image", image);  double minVal, maxVal;  minMaxLoc(image, &minVal, &maxVal);  printf("minVal = %lf\n", minVal);  printf("maxVal = %lf\n", maxVal);  13.角点提取//读取输入图像  Mat image = imread("calibrateGray.bmp");  namedWindow("image");  imshow("image", image);    //检测角点  Mat cornerStrength;  cornerHarris(image, cornerStrength,                       3, //相邻像素的尺寸                      3, //滤波器的孔径大小                      0.01); //Harris参数    //角点强度的阈值  Mat harrisCorners;  double thresholdVal = 0.0001;  threshold(cornerStrength, harrisCorners, thresholdVal, 255, THRESH_BINARY_INV);  namedWindow("harrisCorners");  imshow("harrisCorners", harrisCorners);  imwrite("calibrateHarris.bmp", harrisCorners);  14.判断图像是否读入成功//读取输入图像  Mat image = imread("calibrateGray.bmp");  if (!image.data)  {      printf("读取图像失败\n");  }  15. 将unsigned char*（或BYTE*）封装成Mat类型version 1int width = 0;  int height = 0;  int lineByte = 0;  BYTE* imData = rdWtIm.Read8bitbmp("cam1FstImArSptImage.bmp", &width, &height, &lineByte);  printf("width = %d\n", width);  printf("height = %d\n", height);  printf("lineByte = %d\n", lineByte);    Mat iMat(height, width, CV_8UC1, imData, lineByte);  namedWindow("lena");  imshow("lena", iMat);  version 2RdWtIm rdWtIm;    int width = 0;  int height = 0;  int lineByte = 0;  BYTE* imData = rdWtIm.Read8bitbmp("lena.bmp", &width, &height, &lineByte); //cam1FstImArSptImage  printf("width = %d\n", width);  printf("height = %d\n", height);  printf("lineByte = %d\n", lineByte);    //Scalar scal = 0;  Mat iMat(height, width, CV_8UC1, Scalar(0));  iMat.step = lineByte;  iMat.data = imData;  namedWindow("lena");  imshow("lena", iMat);  16.如何使图像显示窗口能够调节大小void namedWindow(const string& winname, int flags=WINDOW_AUTOSIZE )  将参数：flags设置成WINDOW_NORMAL即可。举例：namedWindow("original image", WINDOW_NORMAL);  imshow("original image", image);  17.如何反转图像灰度，即求图像的负片将图像中每点的灰度变成（255-gray），其中gray是当前点的灰度。void bitwise_not(InputArray src, OutputArray dst, InputArray mask=noArray())  18.利用hough变换检测圆////hough变换检测圆  vector<Vec3f> circles;  HoughCircles(inverse, circles, CV_HOUGH_GRADIENT,                          1, //累加器的分辨率（图像的尺寸/2）                          6, //两个圆之间的最小距离                          100, //Canny高阈值                          5, //最小投票数                          3, 7); //极小极大半径3 10  可以将检测出的圆绘制在图中//绘制圆  vector<Vec3f>::const_iterator itc = circles.begin();  while(itc != circles.end())  {      circle(inverse, Point((*itc)[0], (*itc)[1]), //圆心      (*itc)[2], //半径      Scalar(255), //颜色      2); //厚度      ++itc;  }  

cv::f