图像腐蚀

#include //OpenCV highgui 模块头文件 ~

#include //OpenCV 图像处理头文件

using namespace cv; // 包含 cv 命名空间

int main() //控制台应用程序的入 口 函数，我们的程序从这里开始

{

Mat srclmage = imread("G:\\QQ图片20190428194331.jpg");

imshow("[ 原图 ] ",srclmage);

//进行腐蚀操作

Mat element = getStructuringElement(MORPH_RECT, Size(15, 15));//getStructuringElement函数的返回值为指定形状和尺寸的结构元素(内核矩阵〉

Mat dstlmage;

erode(srclmage, dstlmage, element);

//显示效果图

imshow ("[ 效果图 ] ", dstlmage);

waitKey(0);

return 0;

}

图像模糊

#include //OpenCV highgui 模块头文件 ~

#include //OpenCV 图像处理头文件

using namespace cv; // 包含 cv 命名空间

int main() //控制台应用程序的入 口 函数，我们的程序从这里开始

{

Mat srclmage = imread("G:\\QQ图片20190428194331.jpg");

imshow("[ 原图 ] ",srclmage);

//进行均值滤波操作

Mat dstlmage;

blur(srclmage, dstlmage, Size(7, 7));

imshow ("[ 效果图 ] ", dstlmage);

waitKey(0);

return 0;

}

canny边缘检测

#include

#include //OpenCV 图像处理头文件

using namespace cv; // 包含 cv 命名空间

int main() //控制台应用程序的入 口 函数，我们的程序从这里开始

{

Mat srcImage = imread("G:\\QQ图片20190428194331.jpg");

imshow("[ 原图 ] ",srcImage);

Mat dstImage, edge, grayImage;

//创建与src同类型和大小的矩阵(dst)

dstImage.create(srcImage.size(), srcImage.type());

//将原图像转换为灰度图像,Opencv2

cvtColor(srcImage, grayImage, CV_BGR2GRAY);

/*Opencv3

cvtColor(srcImage,grayImage,COLOR_BGR2GRAY);

*/

//先使用3x3内核来降噪

blur(grayImage, edge, Size(3, 3));

//运行Canny算子

Canny(edge, edge, 3, 9, 3);

//显示

imshow ("[ 效果图 ] ", edge);

waitKey(0);

return 0;

}

读取视频

#include

using namespace cv;

int main()

{

//读入视频

VideoCapture capture("G:\\视觉资料\\【OpenCV3版】《OpenCV3编程入门》书本配套源代码\\【1】书本正篇程序源代码\\【1】第一章\\【6】播放视频\\6_播放视频\\1.avi ");

//循环显示每一帧

while(1)

{

Mat frame;//定义一个Mat变量，用于储存每一帧的图像

capture >> frame;//读取当前帧

imshow("读取视频",frame);//显示当前帧

waitKey(30);//延时30ms

}

return 0;

}

canny从摄像头得到的视频

#include

using namespace cv;

int main()

{

VideoCapture capture(0);

Mat edges;

//循环显示每一帧

while(1)

{

Mat frame;//定义一个Mat变量，用于储存每一帧的图像

capture >> frame;//读取当前帧

cvtColor(frame, edges, CV_BGR2GRAY);

blur(edges, edges, Size(7, 7));

Canny(edges, edges, 0, 30, 3);

imshow("canny后的视频",edges);//显示当前帧

if(waitKey(30)>=0)break;//延时30ms

}

return 0;

}

2.1.1 彩色目标跟踪:Camshift

注意：本代码仅供学习交流所用，所有权归《OpenCV3编程入门》OpenCV3版书，请勿商用

#include "opencv2/video/tracking.hpp"

#include "opencv2/imgproc/imgproc.hpp"

#include "opencv2/highgui/highgui.hpp"

#include

#include

using namespace cv;

using namespace std;

//-----------------------------------【全局变量声明】-----------------------------------------

//描述：声明全局变量

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

Mat image;

bool backprojMode = false;

bool selectObject = false;

int trackObject = 0;

bool showHist = true;

Point origin;

Rect selection;

int vmin = 10, vmax = 256, smin = 30;

//--------------------------------【onMouse( )回调函数】------------------------------------

//描述：鼠标操作回调

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

static void onMouse(int event, int x, int y, int, void*)

{

if (selectObject)

{

selection.x = MIN(x, origin.x);

selection.y = MIN(y, origin.y);

selection.width = std::abs(x - origin.x);

selection.height = std::abs(y - origin.y);

selection &= Rect(0, 0, image.cols, image.rows);

}

switch (event)

{

//此句代码的OpenCV2版为：

//case CV_EVENT_LBUTTONDOWN:

//此句代码的OpenCV3版为：

case EVENT_LBUTTONDOWN:

origin = Point(x, y);

selection = Rect(x, y, 0, 0);

selectObject = true;

break;

//此句代码的OpenCV2版为：

//case CV_EVENT_LBUTTONUP:

//此句代码的OpenCV3版为：

case EVENT_LBUTTONUP:

selectObject = false;

if (selection.width > 0 && selection.height > 0)

trackObject = -1;

break;

}

}

//--------------------------------【help( )函数】----------------------------------------------

//描述：输出帮助信息

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

static void ShowHelpText()

{

cout << "\n\n\t\t\t非常感谢购买《OpenCV3编程入门》一书！\n"

<< "\n\n\t\t\t此为本书OpenCV3版的第8个配套示例程序\n"

<< "\n\n\t\t\t 当前使用的OpenCV版本为：" << CV_VERSION

<< "\n\n ----------------------------------------------------------------------------";

cout << "\n\n\t此Demo显示了基于均值漂移的追踪(tracking)技术\n"

"\t请用鼠标框选一个有颜色的物体，对它进行追踪操作\n";

cout << "\n\n\t操作说明： \n"

"\t\t用鼠标框选对象来初始化跟踪\n"

"\t\tESC - 退出程序\n"

"\t\tc - 停止追踪\n"

"\t\tb - 开/关-投影视图\n"

"\t\th - 显示/隐藏-对象直方图\n"

"\t\tp - 暂停视频\n";

}

const char* keys =

{

"{1| | 0 | camera number}"

};

//-----------------------------------【main( )函数】--------------------------------------------

//描述：控制台应用程序的入口函数，我们的程序从这里开始

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

int main(int argc, const char** argv)

{

ShowHelpText();

VideoCapture cap;

Rect trackWindow;

int hsize = 16;

float hranges[] = { 0,180 };

const float* phranges = hranges;

cap.open(0);

if (!cap.isOpened())

{

cout << "不能初始化摄像头\n";

}

namedWindow("Histogram", 0);

namedWindow("CamShift Demo", 0);

setMouseCallback("CamShift Demo", onMouse, 0);

createTrackbar("Vmin", "CamShift Demo", &vmin, 256, 0);

createTrackbar("Vmax", "CamShift Demo", &vmax, 256, 0);

createTrackbar("Smin", "CamShift Demo", &smin, 256, 0);

Mat frame, hsv, hue, mask, hist, histimg = Mat::zeros(200, 320, CV_8UC3), backproj;

bool paused = false;

for (;;)

{

if (!paused)

{

cap >> frame;

if (frame.empty())

break;

}

frame.copyTo(image);

if (!paused)

{

cvtColor(image, hsv, COLOR_BGR2HSV);

if (trackObject)

{

int _vmin = vmin, _vmax = vmax;

inRange(hsv, Scalar(0, smin, MIN(_vmin, _vmax)),

Scalar(180, 256, MAX(_vmin, _vmax)), mask);

int ch[] = { 0, 0 };

hue.create(hsv.size(), hsv.depth());

mixChannels(&hsv, 1, &hue, 1, ch, 1);

if (trackObject < 0)

{

Mat roi(hue, selection), maskroi(mask, selection);

calcHist(&roi, 1, 0, maskroi, hist, 1, &hsize, &phranges);

//此句代码的OpenCV3版为：

normalize(hist, hist, 0, 255, NORM_MINMAX);

//此句代码的OpenCV2版为：

//normalize(hist, hist, 0, 255, CV_MINMAX);

trackWindow = selection;

trackObject = 1;

histimg = Scalar::all(0);

int binW = histimg.cols / hsize;

Mat buf(1, hsize, CV_8UC3);

for (int i = 0; i < hsize; i++)

buf.at(i) = Vec3b(saturate_cast(i*180. / hsize), 255, 255);

//此句代码的OpenCV3版为：

cvtColor(buf, buf, COLOR_HSV2BGR);

//此句代码的OpenCV2版为：

//cvtColor(buf, buf, CV_HSV2BGR);

for (int i = 0; i < hsize; i++)

{

int val = saturate_cast(hist.at(i)*histimg.rows / 255);

rectangle(histimg, Point(i*binW, histimg.rows),

Point((i + 1)*binW, histimg.rows - val),

Scalar(buf.at(i)), -1, 8);

}

}

calcBackProject(&hue, 1, 0, hist, backproj, &phranges);

backproj &= mask;

RotatedRect trackBox = CamShift(backproj, trackWindow,

//此句代码的OpenCV3版为：

TermCriteria(TermCriteria::EPS | TermCriteria::COUNT, 10, 1));

//此句代码的OpenCV2版为：

//TermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ));

if (trackWindow.area() <= 1)

{

int cols = backproj.cols, rows = backproj.rows, r = (MIN(cols, rows) + 5) / 6;

trackWindow = Rect(trackWindow.x - r, trackWindow.y - r,

trackWindow.x + r, trackWindow.y + r) &

Rect(0, 0, cols, rows);

}

if (backprojMode)

cvtColor(backproj, image, COLOR_GRAY2BGR);

//此句代码的OpenCV3版为：

ellipse(image, trackBox, Scalar(0, 0, 255), 3, LINE_AA);

//此句代码的OpenCV2版为：

//ellipse( image, trackBox, Scalar(0,0,255), 3, CV_AA );

}

}

else if (trackObject < 0)

paused = false;

if (selectObject && selection.width > 0 && selection.height > 0)

{

Mat roi(image, selection);

bitwise_not(roi, roi);

}

imshow("CamShift Demo", image);

imshow("Histogram", histimg);

char c = (char)waitKey(10);

if (c == 27)

break;

switch (c)

{

case 'b':

backprojMode = !backprojMode;

break;

case 'c':

trackObject = 0;

histimg = Scalar::all(0);

break;

case 'h':

showHist = !showHist;

if (!showHist)

destroyWindow("Histogram");

else

namedWindow("Histogram", 1);

break;

case 'p':

paused = !paused;

break;

default:

;

}

}

return 0;

}

9_用光流法进行运动目标检测

//---------------------------------【头文件、命名空间包含部分】----------------------------

//描述：包含程序所使用的头文件和命名空间

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

#include

#include

#include

#include

#include

#include

using namespace std;

using namespace cv;

//-----------------------------------【全局函数声明】-----------------------------------------

//描述：声明全局函数

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

void tracking(Mat &frame, Mat &output);

bool addNewPoints();

bool acceptTrackedPoint(int i);

//-----------------------------------【全局变量声明】-----------------------------------------

//描述：声明全局变量

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

string window_name = "optical flow tracking";

Mat gray;// 当前图片

Mat gray_prev;// 预测图片

vector points[2];// point0为特征点的原来位置，point1为特征点的新位置

vector initial;// 初始化跟踪点的位置

vector features;// 检测的特征

int maxCount = 500;// 检测的最大特征数

double qLevel = 0.01;// 特征检测的等级

double minDist = 10.0;// 两特征点之间的最小距离

vector status;// 跟踪特征的状态，特征的流发现为1，否则为0

vector err;

//--------------------------------【help( )函数】----------------------------------------------

//描述：输出帮助信息

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

static void help()

{

//输出欢迎信息和OpenCV版本

cout <

<

<

<

}

//-----------------------------------【main( )函数】--------------------------------------------

//描述：控制台应用程序的入口函数，我们的程序从这里开始

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

int main()

{

Mat frame;

Mat result;

VideoCapture capture("1.avi");

help();

if(capture.isOpened())// 摄像头读取文件开关

{

while(true)

{

capture >> frame;

if(!frame.empty())

{

tracking(frame, result);

}

else

{

printf(" --(!) No captured frame -- Break!");

break;

}

int c = waitKey(50);

if( (char)c == 27 )

{

break;

}

}

}

return 0;

}

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

// function: tracking

// brief: 跟踪

// parameter: frame输入的视频帧

// output 有跟踪结果的视频帧

// return: void

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

void tracking(Mat &frame, Mat &output)

{

//此句代码的OpenCV3版为：

cvtColor(frame, gray, COLOR_BGR2GRAY);

//此句代码的OpenCV2版为：

//cvtColor(frame, gray, CV_BGR2GRAY);

frame.copyTo(output);

// 添加特征点

if (addNewPoints())

{

goodFeaturesToTrack(gray, features, maxCount, qLevel, minDist);

points[0].insert(points[0].end(), features.begin(), features.end());

initial.insert(initial.end(), features.begin(), features.end());

}

if (gray_prev.empty())

{

gray.copyTo(gray_prev);

}

// l-k光流法运动估计

calcOpticalFlowPyrLK(gray_prev, gray, points[0], points[1], status, err);

// 去掉一些不好的特征点

int k = 0;

for (size_t i=0; i

{

if (acceptTrackedPoint(i))

{

initial[k] = initial[i];

points[1][k++] = points[1][i];

}

}

points[1].resize(k);

initial.resize(k);

// 显示特征点和运动轨迹

for (size_t i=0; i

{

line(output, initial[i], points[1][i], Scalar(0, 0, 255));

circle(output, points[1][i], 3, Scalar(0, 255, 0), -1);

}

// 把当前跟踪结果作为下一此参考

swap(points[1], points[0]);

swap(gray_prev, gray);

imshow(window_name, output);

}

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

// function: addNewPoints

// brief: 检测新点是否应该被添加

// parameter:

// return: 是否被添加标志

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

bool addNewPoints()

{

return points[0].size() <= 10;

}

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

// function: acceptTrackedPoint

// brief: 决定哪些跟踪点被接受

// parameter:

// return:

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

bool acceptTrackedPoint(int i)

{

return status[i] && ((abs(points[0][i].x - points[1][i].x) + abs(points[0][i].y - points[1][i].y)) > 2);

}

点追踪

#include "opencv2/video/tracking.hpp"

#include "opencv2/imgproc/imgproc.hpp"

#include "opencv2/highgui/highgui.hpp"

#include

#include

using namespace cv;

using namespace std;

//--------------------------------【help( )函数】----------------------------------------------

//描述：输出帮助信息

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

static void help()

{

//输出欢迎信息和OpenCV版本

cout << "\n\n\t\t\t非常感谢购买《OpenCV3编程入门》一书！\n"

<< "\n\n\t\t\t此为本书OpenCV3版的第10个配套示例程序\n"

<< "\n\n\t\t\t 当前使用的OpenCV版本为：" << CV_VERSION

<< "\n\n ----------------------------------------------------------------------------";

cout << "\n\n\t该Demo演示了 Lukas-Kanade基于光流的lkdemo\n";

cout << "\n\t程序默认从摄像头读入视频，可以按需改为从视频文件读入图像\n";

cout << "\n\t操作说明: \n"

"\t\t通过点击在图像中添加/删除特征点\n"

"\t\tESC - 退出程序\n"

"\t\tr -自动进行追踪\n"

"\t\tc - 删除所有点\n"

"\t\tn - 开/光-夜晚模式\n" << endl;

}

Point2f point;

bool addRemovePt = false;

//--------------------------------【onMouse( )回调函数】------------------------------------

//描述：鼠标操作回调

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

static void onMouse(int event, int x, int y, int /*flags*/, void* /*param*/)

{

//此句代码的OpenCV2版为：

//if( event == CV_EVENT_LBUTTONDOWN )

//此句代码的OpenCV3版为：

if (event == EVENT_LBUTTONDOWN)

{

point = Point2f((float)x, (float)y);

addRemovePt = true;

}

}

//-----------------------------------【main( )函数】--------------------------------------------

//描述：控制台应用程序的入口函数，我们的程序从这里开始

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

int main(int argc, char** argv)

{

help();

VideoCapture cap;

//此句代码的OpenCV2版为：

//TermCriteria termcrit(CV_TERMCRIT_ITER|CV_TERMCRIT_EPS, 20, 0.03);

//此句代码的OpenCV3版为：

TermCriteria termcrit(TermCriteria::MAX_ITER | TermCriteria::EPS, 20, 0.03);

Size subPixWinSize(10, 10), winSize(31, 31);

const int MAX_COUNT = 500;

bool needToInit = false;

bool nightMode = false;

cap.open(0);

if (!cap.isOpened())

{

cout << "Could not initialize capturing...\n";

return 0;

}

namedWindow("LK Demo", 1);

setMouseCallback("LK Demo", onMouse, 0);

Mat gray, prevGray, image;

vector points[2];

for (;;)

{

Mat frame;

cap >> frame;

if (frame.empty())

break;

frame.copyTo(image);

cvtColor(image, gray, COLOR_BGR2GRAY);

if (nightMode)

image = Scalar::all(0);

if (needToInit)

{

// 自动初始化

goodFeaturesToTrack(gray, points[1], MAX_COUNT, 0.01, (double)10, Mat(), 3,(bool) 0, 0.04);

cornerSubPix(gray, points[1], subPixWinSize, Size(-1, -1), termcrit);

addRemovePt = false;

}

else if (!points[0].empty())

{

vector status;

vector err;

if (prevGray.empty())

gray.copyTo(prevGray);

calcOpticalFlowPyrLK(prevGray, gray, points[0], points[1], status, err, winSize,

3, termcrit, 0, 0.001);

size_t i, k;

for (i = k = 0; i < points[1].size(); i++)

{

if (addRemovePt)

{

if (norm(point - points[1][i]) <= 5)

{

addRemovePt = false;

continue;

}

}

if (!status[i])

continue;

points[1][k++] = points[1][i];

circle(image, points[1][i], 3, Scalar(0, 255, 0), -1, 8);

}

points[1].resize(k);

}

if (addRemovePt && points[1].size() < (size_t)MAX_COUNT)

{

vector tmp;

tmp.push_back(point);

//此句代码的OpenCV2版为：

//cornerSubPix( gray, tmp, winSize, cvSize(-1,-1), termcrit);

//此句代码的OpenCV3版为：

cornerSubPix(gray, tmp, winSize, Size(-1, -1), termcrit);

points[1].push_back(tmp[0]);

addRemovePt = false;

}

needToInit = false;

imshow("LK Demo", image);

char c = (char)waitKey(10);

if (c == 27)

break;

switch (c)

{

case 'r':

needToInit = true;

break;

case 'c':

points[0].clear();

points[1].clear();

break;

case 'n':

nightMode = !nightMode;

break;

}

std::swap(points[1], points[0]);

cv::swap(prevGray, gray);

}

return 0;

}