OpenCV图像处理基础

OpenCV中程序的模板

#include <iostream>#include"opencv2/opencv.hpp"using namespace std;using namespace cv;

在OpenCV中，灰度图像的存储示意图

彩色图像的存储示意图，在OpenCV中彩色图像的颜色存储顺序为蓝，绿，红（BGR）

Mat常用的构造函数

Mat::Mat()Mat::Mat(int rows, int cols, int type)Mat::Mat(Size size, int type)Mat::Mat(int rows, int cols, int type, const Scalar& s)Mat::Mat(Size size, int type, const Scalar& s)Mat::Mat(const Mat& m)Mat::Mat(int rows, int cols, int type, void* data, size_t step=AUTO_STEP)Mat::Mat(Size size, int type, void* data, size_t step=AUTO_STEP)Mat::Mat(const Mat& m, const Range& rowRange, const Range& colRange)Mat::Mat(const Mat& m, const Rect& roi)//构造函数创建图像Mat M(2,2,CV_8UC3);//释放内存重新创建图像M.create(3,2,CV_8UC2);

OpenCV深拷贝和浅拷贝的问题

遍历图像（几种像素值得读写）
方法1

//灰度图像uchar value=grayim.at<uchar>(i,j);for(int i=0;igrayim.rows;++i)   for(int j=0;j<grayim.cols;++j)      grayim.at<uchar>(i,j)=(i+j)%255;//彩色图像for(int i=0;i<colorim.rows;++i)   for(int j=0;j<colorim.cols;++j)   {      Vec3b pixel;      pixel[0]=i%255;  //Blue      pixel[1]=j%255;  //Green      pixel[2]=0;  //Red      colorim.at<Vec3b>(i,j)=pixel;   }

方法2（迭代器）

//灰度图像cv::Mat Iterator_<uchar> grayit, grayend;for( grayit = grayim.begin<uchar>(), grayend = grayim.end<uchar>(); grayit != grayend; ++grayit)    *grayit = rand()%255;//彩色图像cv::Mat Iterator_<Vec3b> colorit,colorend;for(colorit=colorim.begin<Vec3b>(),colorend=colorim.end<Vec3b>();colorit!=colorend;++colorit){    (*colorit)[0]=rand()%255;  //Blue    (*colorit)[1]=rand()%255;  //Green    (*colorit)[2]=rand()%255;  //Red}

方法3

for( int i = 0; i < grayim.rows; ++i){    //获取第 i 行首像素指针    uchar * p = grayim.ptr<uchar>(i);    //对第 i 行的每个像素(byte)操作    for( int j = 0; j < grayim.cols; ++j )         p[j] = (i+j)%255;}

方法4（step）
二维数据

三维数据

addr(Mi0,i1,…im-1) = M.data + M.step[0] * i0 + M.step[1] * i1 + … +M.step[m-1] * im-1 (其中 m = M.dims M的维度)

int main(){    //新建一个uchar类型的单通道矩阵（grayscale image 灰度图）    Mat m(400, 400, CV_8U, Scalar(0));    for (int col = 0; col < 400; col++)    {        for (int row = 195; row < 205; row++)        {            cout << (int)(*(m.data + m.step[0] * row + m.step[1] * col)) << "==>";            //获取第[row,col]个像素点的地址并用*符号解析            *(m.data + m.step[0] * row + m.step[1] * col) = 255;            cout << (int)(*(m.data + m.step[0] * row + m.step[1] * col)) << endl;        }    }    imshow("binary image", m);    cvWaitKey();    return 0;}

int main(){    Mat m = imread("lena.jpg");    Vec3i color;    for (int col = 20; col < 40; col++)        for (int row = 5; row < 25; row++)        {            color[0] = (int)(*(m.data + m.step[0] * row + m.step[1] * col));            color[1] = (int)(*(m.data + m.step[0] * row + m.step[1] * col + m.elemSize1()));            color[2] = (int)(*(m.data + m.step[0] * row + m.step[1] * col + m.elemSize1() * 2));            //获取第[row,col]个像素点的地址并用*符号解析            cout << color[0] << "," << color[1] << "," << color[2] << "==>";            color[0] = 255;            color[1] = 0;            color[2] = 0;            *(m.data + m.step[0] * row + m.step[1] * col) = color[0];            *(m.data + m.step[0] * row + m.step[1] * col + m.elemSize1()) = color[1];            *(m.data + m.step[0] * row + m.step[1] * col + m.elemSize1() * 2) = color[2];            cout << (int)*(m.data + m.step[0] * row + m.step[1] * col) <<                (int)*(m.data + m.step[0] * row + m.step[1] * col + 1) <<                (int)*(m.data + m.step[0] * row + m.step[1] * col + 2) << endl;        }    imshow("lena", m);    cvWaitKey();    return 0;}

方法5（Mat_类）

Mat M(600, 800, CV_8UC1);for (int i = 0; i < M.rows; ++i){    uchar * p = M.ptr<uchar>(i);    for (int j = 0; j < M.cols; ++j)    {        double d1 = (double)((i + j) % 255);        M.at<uchar>(i, j) = d1;        double d2 = M.at<double>(i, j);    }}

Mat_<uchar> M1 = (Mat_<uchar>&)M;for (int i = 0; i < M1.rows; ++i){    uchar * p = M1.ptr(i);    for (int j = 0; j < M1.cols; ++j)    {        double d1 = (double)((i + j) % 255);        M1(i, j) = d1;        double d2 = M1(i, j);    }}

int main(){Mat m = imread("lena.jpg");    Mat_<Vec3b>m2 = m;    //for循环画一个蓝色的实心圆    for (int y = 21; y < 42; y++)        for (int x = 2; x < 21; x++)        {            if (pow(double(x - 11), 2) + pow(double(y - 31), 2) - 64 < 0.0000000001)            {                //Mat_模板类实现了对()的重载，可以定位到一个像素                m2(x, y) = Vec3b(255, 0, 0);            }        }    imshow("CircleImage", m2);    cvWaitKey();    return 0;}

方法6

int divideWith=10;uchar table[256];for (int i = 0; i < 256; ++i)    table[i] = divideWith* (i/divideWith); //量化

Mat lookUpTable(1, 256, CV_8U);uchar* p = lookUpTable.data;for( int i = 0; i < 256; ++i)    p[i] = table[i];LUT(I, lookUpTable, Out);

学习OpenCV必备资料

手册：http://docs.opencv.org/
教程：http://docs.opencv.org/2.4/doc/tutorials/tutorials.html
进阶：http://github.com/opencv/opencv/wiki
在OpenCV安装目录下build->doc->opencv_tutorials.pdf 为学习教程