顯示圖像

#include "StdAfx.h" #include <string> #include <iostream> #include <opencv2\core\core.hpp> #include <opencv2\highgui\highgui.hpp>using namespace cv; using namespace std;int main() {string imageName = “lena.jpg”;//讀入圖像Mat img = imread(imageName, CV_LOAD_IMAGE_COLOR);//如果讀入圖像失敗if (img.empty()){cout<<”Could not open or find the image!”<<endl;return -1;}//創建窗口namedWindow(“lena”, CV_WINDOW_AUTOSIZE);//顯示圖像imshow(“lena”, img);//等待按鍵，按鍵盤任意鍵返回waitKey();return 0; }

加載-RGB轉灰度圖-保存

#include “StdAfx.h” #include <cv.h> #include <highgui.h> #include <string>using namespace cv; using namespace std;int main() {char* imageName = “lena.jpg”;Mat image = imread(imageName, 1);if (!image.data){cout<<”Could not open or find the image!”<<endl;return -1;}Mat gray_image;String grayImageName = “lena_gray”;cvtColor(image,gray_image,CV_RGB2GRAY);//將RGB圖像轉換成灰度圖像imwrite(“../../lena_gray.jpg”,gray_image);//保存圖像namedWindow(imageName, CV_WINDOW_AUTOSIZE);//創建用于顯示元圖像窗口namedWindow(grayImageName,CV_WINDOW_AUTOSIZE);//創建用于顯示轉換后圖像窗口imshow(imageName,image);imshow(“grayImageName”, gray_image);waitKey(0);return 0; } <h1>膨脹操作示例</h1><pre name="code" class="cpp">#include <opencv2/core/core.hpp> #include<opencv2/highgui/highgui.hpp> #include<opencv2/imgproc/imgproc.hpp> #include <iostream>using namespace std; using namespace cv;int main( ) {//載入原圖 Mat image = imread("1.jpg");//創建窗口 namedWindow("原圖-膨脹操作");namedWindow("效果圖-膨脹操作");//顯示原圖imshow("原圖-膨脹操作", image);//獲取自定義核Mat element = getStructuringElement(MORPH_RECT, Size(15, 15));Mat out;//進行膨脹操作dilate(image,out, element);//顯示效果圖imshow("效果圖-膨脹操作", out);waitKey(0);return 0; }

腐蝕操作示例

#include <opencv2/core/core.hpp>

#include<opencv2/highgui/highgui.hpp> #include<opencv2/imgproc/imgproc.hpp> #include <iostream>using namespace std; using namespace cv;int main( ) {//載入原圖 Matimage = imread("1.jpg");//創建窗口 namedWindow("原圖-腐蝕操作");namedWindow("效果圖-腐蝕操作");//顯示原圖imshow("原圖-腐蝕操作", image);//獲取自定義核Mat element = getStructuringElement(MORPH_RECT, Size(15, 15));Mat out;//進行腐蝕操作erode(image,out, element);//顯示效果圖imshow("效果圖-腐蝕操作", out);waitKey(0);return 0; }

膨脹與腐蝕綜合示例

#include <opencv2/opencv.hpp> #include <opencv2/highgui/highgui.hpp> #include<opencv2/imgproc/imgproc.hpp> #include <iostream>using namespace std; using namespace cv;Mat g_srcImage, g_dstImage;//原始圖和效果圖 int g_nTrackbarNumer = 0;//0表示腐蝕erode, 1表示膨脹dilate int g_nStructElementSize = 3; //結構元素(內核矩陣)的尺寸void Process();//膨脹和腐蝕的處理函數 void on_TrackbarNumChange(int, void *);//回調函數 void on_ElementSizeChange(int, void *);//回調函數int main( ) {//改變console字體顏色system("color5E"); //載入原圖g_srcImage= imread("1.jpg");if(!g_srcImage.data ) { printf("Oh，no，讀取srcImage錯誤~！\n"); return false; }//顯示原始圖namedWindow("原始圖");imshow("原始圖", g_srcImage);//進行初次腐蝕操作并顯示效果圖namedWindow("效果圖");//獲取自定義核Matelement = getStructuringElement(MORPH_RECT, Size(2*g_nStructElementSize+1,2*g_nStructElementSize+1),Point( g_nStructElementSize, g_nStructElementSize ));erode(g_srcImage,g_dstImage, element);imshow("效果圖", g_dstImage);//創建軌跡條createTrackbar("腐蝕/膨脹", "效果圖", &g_nTrackbarNumer, 1, on_TrackbarNumChange);createTrackbar("內核尺寸", "效果圖",&g_nStructElementSize, 21, on_ElementSizeChange);//輸出一些幫助信息cout<<endl<<"\t嗯。運行成功，請調整滾動條觀察圖像效果~\n\n"<<"\t按下“q”鍵時，程序退出~!\n"<<"\n\n\t\t\t\tby毛毛";//輪詢獲取按鍵信息，若下q鍵，程序退出while(char(waitKey(1))!= 'q') {}return 0; }//進行自定義的腐蝕和膨脹操作 void Process() {//獲取自定義核Mat element = getStructuringElement(MORPH_RECT, Size(2*g_nStructElementSize+1,2*g_nStructElementSize+1),Point( g_nStructElementSize, g_nStructElementSize ));//進行腐蝕或膨脹操作if(g_nTrackbarNumer== 0) { erode(g_srcImage,g_dstImage, element);}else{dilate(g_srcImage,g_dstImage, element);}//顯示效果圖imshow("效果圖", g_dstImage); }//腐蝕和膨脹之間切換開關的回調函數 void on_TrackbarNumChange(int, void *) {//腐蝕和膨脹之間效果已經切換，回調函數體內需調用一次Process函數，使改變后的效果立即生效并顯示出來Process(); }//腐蝕和膨脹操作內核改變時的回調函數 void on_ElementSizeChange(int, void *) {//內核尺寸已改變，回調函數體內需調用一次Process函數，使改變后的效果立即生效并顯示出來Process(); }

膨脹與腐蝕綜合示例2

#include "cv.h" #include "highgui.h" #include "opencv2/imgproc/imgproc.hpp"using namespace std; using namespace cv;#define TYPE_MORPH_RECT (0) #define TYPE_MORPH_CROSS (1) #define TYPE_MORPH_ELLIPSE (2)#define MAX_ELE_TYPE (2) #define MAX_ELE_SIZE (20)Mat src, erode_dst, dilate_dst;const char *erode_wn = "eroding demo"; const char *dilate_wn = "dilating demo";int erode_ele_type; int dilate_ele_type; int erode_ele_size; int dilate_ele_size;static void Erosion(int, void *); static void Dilation(int, void *);/** @brief * @inputs * @outputs * @retval */ int main(int argc, char *argv[]) {if (argc < 2) {cout<<"Usage: ./eroding_and_dilating [file name]"<<endl;return -1;}src = imread(argv[1]);if (!src.data) {cout<<"Read image failure."<<endl;return -1;}// WindowsnamedWindow(erode_wn, WINDOW_AUTOSIZE);namedWindow(dilate_wn, WINDOW_AUTOSIZE);// Track Bar for ErosioncreateTrackbar("Element Type\n0:Rect\n1:Cross\n2:Ellipse", erode_wn, &erode_ele_type, MAX_ELE_TYPE, Erosion); // callback @ErosioncreateTrackbar("Element Size: 2n+1", erode_wn, &erode_ele_size, MAX_ELE_SIZE, Erosion);// Track Bar for DilationcreateTrackbar("Element Type\n0:Rect\n1:Cross\n2:Ellipse", dilate_wn, &dilate_ele_type, MAX_ELE_TYPE, Dilation); // callback @ErosioncreateTrackbar("Element Size: 2n+1", dilate_wn, &dilate_ele_size, MAX_ELE_SIZE, Dilation);// Default startErosion(0, 0);Dilation(0, 0);waitKey(0);return 0; }/** @brief 腐蝕操作的回調函數* @inputs * @outputs * @retval */ static void Erosion(int, void *) {int erode_type;switch (erode_ele_type) {case TYPE_MORPH_RECT:erode_type = MORPH_RECT; break;case TYPE_MORPH_CROSS:erode_type = MORPH_CROSS;break;case TYPE_MORPH_ELLIPSE:erode_type = MORPH_ELLIPSE;break;default:erode_type = MORPH_RECT;break;}Mat ele = getStructuringElement(erode_type, Size(2*erode_ele_size+1, 2*erode_ele_size+1), Point(erode_ele_size, erode_ele_size));erode(src, erode_dst, ele);imshow(erode_wn, erode_dst); }/** @brief 膨脹操作的回調函數* @inputs * @outputs * @retval */ static void Dilation(int, void *) {int dilate_type;switch (dilate_ele_type) {case TYPE_MORPH_RECT:dilate_type = MORPH_RECT; break;case TYPE_MORPH_CROSS:dilate_type = MORPH_CROSS;break;case TYPE_MORPH_ELLIPSE:dilate_type = MORPH_ELLIPSE;break;default:dilate_type = MORPH_RECT;break;}Mat ele = getStructuringElement(dilate_type, Size(2*dilate_ele_size+1, 2*dilate_ele_size+1), Point(dilate_ele_size, dilate_ele_size));dilate(src, dilate_dst, ele);imshow(dilate_wn, dilate_dst); }

Qt圖像的縮放顯示

#include "widget.h" #include "ui_widget.h" #include <QDebug> Widget::Widget(QWidget *parent) :QWidget(parent),ui(new Ui::Widget) {ui->setupUi(this); }Widget::~Widget() {delete ui; }void Widget::on_openButton_clicked() {QString fileName = QFileDialog::getOpenFileName(this,tr("Open Image"),".",tr("Image Files (*.png *.jpg *.bmp)"));qDebug()<<"filenames:"<<fileName;image = cv::imread(fileName.toAscii().data());ui->imgfilelabel->setText(fileName);//here use 2 ways to make a copy // image.copyTo(originalimg); //make a copyoriginalimg = image.clone(); //clone the imgqimg = Widget::Mat2QImage(image);display(qimg); //display by the labelif(image.data){ui->saltButton->setEnabled(true);ui->originalButton->setEnabled(true);ui->reduceButton->setEnabled(true);} }QImage Widget::Mat2QImage(const cv::Mat &mat) {QImage img;if(mat.channels()==3){//cvt Mat BGR 2 QImage RGBcvtColor(mat,rgb,CV_BGR2RGB);img =QImage((const unsigned char*)(rgb.data),rgb.cols,rgb.rows,rgb.cols*rgb.channels(),QImage::Format_RGB888);}else{img =QImage((const unsigned char*)(mat.data),mat.cols,mat.rows,mat.cols*mat.channels(),QImage::Format_RGB888);}return img; }void Widget::display(QImage img) {QImage imgScaled;imgScaled = img.scaled(ui->imagelabel->size(),Qt::KeepAspectRatio); // imgScaled = img.QImage::scaled(ui->imagelabel->width(),ui->imagelabel->height(),Qt::KeepAspectRatio);ui->imagelabel->setPixmap(QPixmap::fromImage(imgScaled)); }void Widget::on_originalButton_clicked() {qimg = Widget::Mat2QImage(originalimg);display(qimg); }void Widget::on_saltButton_clicked() {salt(image,3000);qimg = Widget::Mat2QImage(image);display(qimg); } void Widget::on_reduceButton_clicked() {colorReduce0(image,64);qimg = Widget::Mat2QImage(image);display(qimg); } void Widget::salt(cv::Mat &image, int n) {int i,j;for (int k=0; k<n; k++){i= qrand()%image.cols;j= qrand()%image.rows;if (image.channels() == 1){ // gray-level imageimage.at<uchar>(j,i)= 255;}else if (image.channels() == 3){ // color imageimage.at<cv::Vec3b>(j,i)[0]= 255;image.at<cv::Vec3b>(j,i)[1]= 255;image.at<cv::Vec3b>(j,i)[2]= 255;}} }// using .ptr and [] void Widget::colorReduce0(cv::Mat &image, int div) {int nl= image.rows; // number of linesint nc= image.cols * image.channels(); // total number of elements per linefor (int j=0; j<nl; j++){uchar* data= image.ptr<uchar>(j);for (int i=0; i<nc; i++){// process each pixel ---------------------data[i]= data[i]/div*div+div/2;// end of pixel processing ----------------} // end of line} }
#ifndef WIDGET_H #define WIDGET_H#include <QWidget> #include <QImage> #include <QFileDialog> #include <QTimer> #include <opencv2/core/core.hpp> #include <opencv2/highgui/highgui.hpp> #include <opencv2/imgproc/imgproc.hpp>using namespace cv;namespace Ui { class Widget; }class Widget : public QWidget {Q_OBJECTpublic:explicit Widget(QWidget *parent = 0);~Widget(); private slots:void on_openButton_clicked();QImage Mat2QImage(const cv::Mat &mat);void display(QImage image);void salt(cv::Mat &image, int n);void on_saltButton_clicked();void on_reduceButton_clicked();void colorReduce0(cv::Mat &image, int div);void on_originalButton_clicked();private:Ui::Widget *ui;cv::Mat image;cv::Mat originalimg; //store the original imgQImage qimg;QImage imgScaled;cv::Mat rgb; };#endif // WIDGET_H
#include <iostream>#include <opencv2/core/core.hpp> #include <opencv2/highgui/highgui.hpp>// using .ptr and [] void colorReduce0(cv::Mat &image, int div=64) {int nl= image.rows; // number of linesint nc= image.cols * image.channels(); // total number of elements per linefor (int j=0; j<nl; j++) {uchar* data= image.ptr<uchar>(j);for (int i=0; i<nc; i++) {// process each pixel ---------------------data[i]= data[i]/div*div + div/2;// end of pixel processing ----------------} // end of line } }// using .ptr and * ++ void colorReduce1(cv::Mat &image, int div=64) {int nl= image.rows; // number of linesint nc= image.cols * image.channels(); // total number of elements per linefor (int j=0; j<nl; j++) {uchar* data= image.ptr<uchar>(j);for (int i=0; i<nc; i++) {// process each pixel ---------------------*data++= *data/div*div + div/2;// end of pixel processing ----------------} // end of line } }// using .ptr and * ++ and modulo void colorReduce2(cv::Mat &image, int div=64) {int nl= image.rows; // number of linesint nc= image.cols * image.channels(); // total number of elements per linefor (int j=0; j<nl; j++) {uchar* data= image.ptr<uchar>(j);for (int i=0; i<nc; i++) {// process each pixel ---------------------int v= *data;*data++= v - v%div + div/2;// end of pixel processing ----------------} // end of line } }// using .ptr and * ++ and bitwise void colorReduce3(cv::Mat &image, int div=64) {int nl= image.rows; // number of linesint nc= image.cols * image.channels(); // total number of elements per lineint n= static_cast<int>(log(static_cast<double>(div))/log(2.0));// mask used to round the pixel valueuchar mask= 0xFF<<n; // e.g. for div=16, mask= 0xF0for (int j=0; j<nl; j++) {uchar* data= image.ptr<uchar>(j);for (int i=0; i<nc; i++) {// process each pixel ---------------------*data++= *data&mask + div/2;// end of pixel processing ----------------} // end of line } }// direct pointer arithmetic void colorReduce4(cv::Mat &image, int div=64) {int nl= image.rows; // number of linesint nc= image.cols * image.channels(); // total number of elements per lineint n= static_cast<int>(log(static_cast<double>(div))/log(2.0));int step= image.step; // effective width// mask used to round the pixel valueuchar mask= 0xFF<<n; // e.g. for div=16, mask= 0xF0// get the pointer to the image bufferuchar *data= image.data;for (int j=0; j<nl; j++) {for (int i=0; i<nc; i++) {// process each pixel ---------------------*(data+i)= *data&mask + div/2;// end of pixel processing ----------------} // end of line data+= step; // next line} }// using .ptr and * ++ and bitwise with image.cols * image.channels() void colorReduce5(cv::Mat &image, int div=64) {int nl= image.rows; // number of linesint n= static_cast<int>(log(static_cast<double>(div))/log(2.0));// mask used to round the pixel valueuchar mask= 0xFF<<n; // e.g. for div=16, mask= 0xF0for (int j=0; j<nl; j++) {uchar* data= image.ptr<uchar>(j);for (int i=0; i<image.cols * image.channels(); i++) {// process each pixel ---------------------*data++= *data&mask + div/2;// end of pixel processing ----------------} // end of line } }// using .ptr and * ++ and bitwise (continuous) void colorReduce6(cv::Mat &image, int div=64) {int nl= image.rows; // number of linesint nc= image.cols * image.channels(); // total number of elements per lineif (image.isContinuous()) {// then no padded pixelsnc= nc*nl; nl= 1; // it is now a 1D array}int n= static_cast<int>(log(static_cast<double>(div))/log(2.0));// mask used to round the pixel valueuchar mask= 0xFF<<n; // e.g. for div=16, mask= 0xF0for (int j=0; j<nl; j++) {uchar* data= image.ptr<uchar>(j);for (int i=0; i<nc; i++) {// process each pixel ---------------------*data++= *data&mask + div/2;// end of pixel processing ----------------} // end of line } }// using .ptr and * ++ and bitwise (continuous+channels) void colorReduce7(cv::Mat &image, int div=64) {int nl= image.rows; // number of linesint nc= image.cols ; // number of columnsif (image.isContinuous()) {// then no padded pixelsnc= nc*nl; nl= 1; // it is now a 1D array}int n= static_cast<int>(log(static_cast<double>(div))/log(2.0));// mask used to round the pixel valueuchar mask= 0xFF<<n; // e.g. for div=16, mask= 0xF0for (int j=0; j<nl; j++) {uchar* data= image.ptr<uchar>(j);for (int i=0; i<nc; i++) {// process each pixel ---------------------*data++= *data&mask + div/2;*data++= *data&mask + div/2;*data++= *data&mask + div/2;// end of pixel processing ----------------} // end of line } }// using Mat_ iterator void colorReduce8(cv::Mat &image, int div=64) {// get iteratorscv::Mat_<cv::Vec3b>::iterator it= image.begin<cv::Vec3b>();cv::Mat_<cv::Vec3b>::iterator itend= image.end<cv::Vec3b>();for ( ; it!= itend; ++it) {// process each pixel ---------------------(*it)[0]= (*it)[0]/div*div + div/2;(*it)[1]= (*it)[1]/div*div + div/2;(*it)[2]= (*it)[2]/div*div + div/2;// end of pixel processing ----------------} }// using Mat_ iterator and bitwise void colorReduce9(cv::Mat &image, int div=64) {// div must be a power of 2int n= static_cast<int>(log(static_cast<double>(div))/log(2.0));// mask used to round the pixel valueuchar mask= 0xFF<<n; // e.g. for div=16, mask= 0xF0// get iteratorscv::Mat_<cv::Vec3b>::iterator it= image.begin<cv::Vec3b>();cv::Mat_<cv::Vec3b>::iterator itend= image.end<cv::Vec3b>();// scan all pixelsfor ( ; it!= itend; ++it) {// process each pixel ---------------------(*it)[0]= (*it)[0]&mask + div/2;(*it)[1]= (*it)[1]&mask + div/2;(*it)[2]= (*it)[2]&mask + div/2;// end of pixel processing ----------------} }// using MatIterator_ void colorReduce10(cv::Mat &image, int div=64) {// get iteratorscv::Mat_<cv::Vec3b> cimage= image;cv::Mat_<cv::Vec3b>::iterator it=cimage.begin();cv::Mat_<cv::Vec3b>::iterator itend=cimage.end();for ( ; it!= itend; it++) { // process each pixel ---------------------(*it)[0]= (*it)[0]/div*div + div/2;(*it)[1]= (*it)[1]/div*div + div/2;(*it)[2]= (*it)[2]/div*div + div/2;// end of pixel processing ----------------} }void colorReduce11(cv::Mat &image, int div=64) {int nl= image.rows; // number of linesint nc= image.cols; // number of columnsfor (int j=0; j<nl; j++) {for (int i=0; i<nc; i++) {// process each pixel ---------------------image.at<cv::Vec3b>(j,i)[0]=image.at<cv::Vec3b>(j,i)[0]/div*div + div/2;image.at<cv::Vec3b>(j,i)[1]=image.at<cv::Vec3b>(j,i)[1]/div*div + div/2;image.at<cv::Vec3b>(j,i)[2]=image.at<cv::Vec3b>(j,i)[2]/div*div + div/2;// end of pixel processing ----------------} // end of line } }// with input/ouput images void colorReduce12(const cv::Mat &image, // input image cv::Mat &result, // output imageint div=64) {int nl= image.rows; // number of linesint nc= image.cols ; // number of columns// allocate output image if necessaryresult.create(image.rows,image.cols,image.type());// created images have no padded pixelsnc= nc*nl; nl= 1; // it is now a 1D arrayint n= static_cast<int>(log(static_cast<double>(div))/log(2.0));// mask used to round the pixel valueuchar mask= 0xFF<<n; // e.g. for div=16, mask= 0xF0for (int j=0; j<nl; j++) {uchar* data= result.ptr<uchar>(j);const uchar* idata= image.ptr<uchar>(j);for (int i=0; i<nc; i++) { // process each pixel ---------------------*data++= (*idata++)&mask + div/2;*data++= (*idata++)&mask + div/2;*data++= (*idata++)&mask + div/2;// end of pixel processing ---------------- } // end of line } }// using overloaded operators void colorReduce13(cv::Mat &image, int div=64) { int n= static_cast<int>(log(static_cast<double>(div))/log(2.0));// mask used to round the pixel valueuchar mask= 0xFF<<n; // e.g. for div=16, mask= 0xF0// perform color reductionimage=(image&cv::Scalar(mask,mask,mask))+cv::Scalar(div/2,div/2,div/2); }

圖像銳化1

sharp.h

#pragma once #include <opencv\cv.h> using namespace cv; namespace ggicci {void sharpen(const Mat& img, Mat& result); }
sharp.cpp #include "sharp.h" void ggicci::sharpen(const Mat& img, Mat& result) { result.create(img.size(), img.type());//處理邊界內部的像素點, 圖像最外圍的像素點應該額外處理for (int row = 1; row < img.rows-1; row++){//前一行像素點const uchar* previous = img.ptr<const uchar>(row-1);//待處理的當前行const uchar* current = img.ptr<const uchar>(row);//下一行const uchar* next = img.ptr<const uchar>(row+1);uchar *output = result.ptr<uchar>(row);int ch = img.channels();int starts = ch;int ends = (img.cols - 1) * ch;for (int col = starts; col < ends; col++){//輸出圖像的遍歷指針與當前行的指針同步遞增, 以每行的每一個像素點的每一個通道值為一個遞增量, 因為要考慮到圖像的通道數*output++ = saturate_cast<uchar>(5 * current[col] - current[col-ch] - current[col+ch] - previous[col] - next[col]);}} //end loop//處理邊界, 外圍像素點設為 0result.row(0).setTo(Scalar::all(0));result.row(result.rows-1).setTo(Scalar::all(0));result.col(0).setTo(Scalar::all(0));result.col(result.cols-1).setTo(Scalar::all(0)); }
main.cpp #include <opencv\highgui.h> #pragma comment(lib, "opencv_core231d.lib") #pragma comment(lib, "opencv_highgui231d.lib") #pragma comment(lib, "opencv_imgproc231d.lib")using namespace cv;#include "sharp.h"int main() { Mat lena = imread("lena.jpg");Mat sharpenedLena;ggicci::sharpen(lena, sharpenedLena);imshow("lena", lena);imshow("sharpened lena", sharpenedLena);cvWaitKey();return 0; }

圖像銳化2

int main() { Mat lena = imread("lena.jpg");Mat sharpenedLena;Mat kernel = (Mat_<float>(3, 3) << 0, -1, 0, -1, 5, -1, 0, -1, 0);cv::filter2D(lena, sharpenedLena, lena.depth(), kernel);imshow("lena", lena);imshow("sharpened lena", sharpenedLena);cvWaitKey();return 0; }

簡單的灰度圖像的直方圖計算

int main(){ Mat img = imread("lena.jpg", CV_LOAD_IMAGE_GRAYSCALE);Mat* arrays = &img;int narrays = 1;int channels[] = { 0 };InputArray mask = noArray();Mat hist;int dims = 1;int histSize[] = { 256 }; float hranges[] = { 0.0, 255.0 };const float *ranges[] = { hranges };//調用 calcHist 計算直方圖, 結果存放在 hist 中calcHist(arrays, narrays, channels, mask, hist, dims, histSize, ranges);//調用一個我自己寫的簡單的函數用于獲取一張顯示直方圖數據的圖片,//輸入參數為直方圖數據 hist 和期望得到的圖片的尺寸Mat histImg = ggicci::getHistogram1DImage(hist, Size(600, 420));imshow("lena gray image histogram", histImg);waitKey();}Mat ggicci::getHistogram1DImage(const Mat& hist, Size imgSize){Mat histImg(imgSize, CV_8UC3);int Padding = 10;int W = imgSize.width - 2 * Padding;int H = imgSize.height - 2 * Padding;double _max;minMaxLoc(hist, NULL, &_max);double Per = (double)H / _max;const Point Orig(Padding, imgSize.height-Padding);int bin = W / (hist.rows + 2);//畫方柱for (int i = 1; i <= hist.rows; i++){Point pBottom(Orig.x + i * bin, Orig.y);Point pTop(pBottom.x, pBottom.y - Per * hist.at<float>(i-1));line(histImg, pBottom, pTop, Scalar(255, 0, 0), bin);}//畫 3 條紅線標明區域line(histImg, Point(Orig.x + bin, Orig.y - H), Point(Orig.x + hist.rows * bin, Orig.y - H), Scalar(0, 0, 255), 1);line(histImg, Point(Orig.x + bin, Orig.y), Point(Orig.x + bin, Orig.y - H), Scalar(0, 0, 255), 1);line(histImg, Point(Orig.x + hist.rows * bin, Orig.y), Point(Orig.x + hist.rows * bin, Orig.y - H), Scalar(0, 0, 255), 1);drawArrow(histImg, Orig, Orig+Point(W, 0), 10, 30, Scalar::all(0), 2);drawArrow(histImg, Orig, Orig-Point(0, H), 10, 30, Scalar::all(0), 2);return histImg;}

圖像縮放-最近鄰插值-雙線性插值

#include "stdafx.h" #include <cv.h> #include <cxcore.h> #include <highgui.h> #include <cmath>using namespace std; using namespace cv;int main(int argc ,char ** argv) {IplImage *scr=0;IplImage *dst=0;double scale=4;CvSize dst_cvsize;if (argc==2&&(scr=cvLoadImage(argv[1],-1))!=0){dst_cvsize.width=(int)(scr->width*scale);dst_cvsize.height=(int)(scr->height*scale);dst=cvCreateImage(dst_cvsize,scr->depth,scr->nChannels);cvResize(scr,dst,CV_INTER_NN);// // CV_INTER_NN - 最近鄰插值, // CV_INTER_LINEAR - 雙線性插值 (缺省使用) // CV_INTER_AREA - 使用象素關系重采樣。當圖像縮小時候，該方法可以避免波紋出現。/*當圖像放大時，類似于 CV_INTER_NN 方法..*/ // CV_INTER_CUBIC - 立方插值.cvNamedWindow("scr",CV_WINDOW_AUTOSIZE);cvNamedWindow("dst",CV_WINDOW_AUTOSIZE);cvShowImage("scr",scr);cvShowImage("dst",dst);cvWaitKey();cvReleaseImage(&scr);cvReleaseImage(&dst);cvDestroyWindow("scr");cvDestroyWindow("dst");}return 0; }

圖片加“懷舊色”濾鏡保存輸出

#include <opencv/cv.h> #include <opencv/highgui.h>using namespace cv; using namespace std;int main(int argc, char ** argv) {// input args checkif(argc < 3){printf("please input args.\n");printf("e.g. : ./test infilepath outfilepath \n");return 0;}char * input = argv[1];char * output = argv[2];printf("input: %s, output: %s\n", input, output);Mat src = imread(input, 1);int width=src.cols;int heigh=src.rows;RNG rng;Mat img(src.size(),CV_8UC3);for (int y=0; y<heigh; y++){uchar* P0 = src.ptr<uchar>(y);uchar* P1 = img.ptr<uchar>(y);for (int x=0; x<width; x++){float B=P0[3*x];float G=P0[3*x+1];float R=P0[3*x+2];float newB=0.272*R+0.534*G+0.131*B;float newG=0.349*R+0.686*G+0.168*B;float newR=0.393*R+0.769*G+0.189*B;if(newB<0)newB=0;if(newB>255)newB=255;if(newG<0)newG=0;if(newG>255)newG=255;if(newR<0)newR=0;if(newR>255)newR=255;P1[3*x] = (uchar)newB;P1[3*x+1] = (uchar)newG;P1[3*x+2] = (uchar)newR;}}//imshow("out",img);waitKey();imwrite(output,img); }

浮雕和雕刻效果

#include <cv.h> #include <highgui.h> #pragma comment( lib, "cv.lib" ) #pragma comment( lib, "cxcore.lib" ) #pragma comment( lib, "highgui.lib" ) int main() { IplImage *org=cvLoadImage("1.jpg",1); IplImage *image=cvCloneImage(org); int width=image->width; int height=image->height; int step=image->widthStep; int channel=image->nChannels; uchar* data=(uchar *)image->imageData; for(int i=0;i<width-1;i++) { for(int j=0;j<height-1;j++) { for(int k=0;k<channel;k++) { int temp = data[(j+1)*step+(i+1)*channel+k]-data[j*step+i*channel+k]+128;//浮雕 //int temp = data[j*step+i*channel+k]-data[(j+1)*step+(i+1)*channel+k]+128;//雕刻 if(temp>255) { data[j*step+i*channel+k]=255; } else if(temp<0) { data[j*step+i*channel+k]=0; } else { data[j*step+i*channel+k]=temp; } } } } cvNamedWindow("original",1); cvShowImage("original",org); cvNamedWindow("image",1); cvShowImage("image",image); cvWaitKey(0); cvDestroyAllWindows(); cvReleaseImage(&image); cvReleaseImage(&org); return 0; }

圖像褶皺效果

#include <cv.h> #include <highgui.h> #pragma comment( lib, "cv.lib" ) #pragma comment( lib, "cxcore.lib" ) #pragma comment( lib, "highgui.lib" ) int main() { IplImage *org=cvLoadImage("lena.jpg",1); IplImage *image=cvCloneImage(org); int width=image->width; int height=image->height; int step=image->widthStep; int channel=image->nChannels; uchar* data=(uchar *)image->imageData; int sign=-1; for(int i=0;i<height;i++) { int cycle=10; int margin=(i%cycle); if((i/cycle)%2==0) { sign=-1; } else { sign=1; } if(sign==-1) { margin=cycle-margin; for(int j=0;j<width-margin;j++) { for(int k=0;k<channel;k++) { data[i*step+j*channel+k]=data[i*step+(j+margin)*channel+k]; } } } else if(sign==1) { for(int j=0;j<width-margin;j++) { for(int k=0;k<channel;k++) { data[i*step+j*channel+k]=data[i*step+(j+margin)*channel+k]; } } } } cvNamedWindow("original",1); cvShowImage("original",org); cvNamedWindow("image",1); cvShowImage("image",image); cvSaveImage("image.jpg",image); cvWaitKey(0); cvDestroyAllWindows(); cvReleaseImage(&image); cvReleaseImage(&org); return 0; }

Grabcut算法

#include "stdafx.h" #include "opencv2/highgui/highgui.hpp" #include "opencv2/imgproc/imgproc.hpp" #include <iostream> #include "ComputeTime.h" #include "windows.h" using namespace std; using namespace cv; static void help() { cout << "\nThis program demonstrates GrabCut segmentation -- select an object in a region\n" "and then grabcut will attempt to segment it out.\n" "Call:\n" "./grabcut <image_name>\n" "\nSelect a rectangular area around the object you want to segment\n" << "\nHot keys: \n" "\tESC - quit the program\n" "\tr - restore the original image\n" "\tn - next iteration\n" "\n" "\tleft mouse button - set rectangle\n" "\n" "\tCTRL+left mouse button - set GC_BGD pixels\n" "\tSHIFT+left mouse button - set CG_FGD pixels\n" "\n" "\tCTRL+right mouse button - set GC_PR_BGD pixels\n" "\tSHIFT+right mouse button - set CG_PR_FGD pixels\n" << endl; } const Scalar RED = Scalar(0,0,255); const Scalar PINK = Scalar(230,130,255); const Scalar BLUE = Scalar(255,0,0); const Scalar LIGHTBLUE = Scalar(255,255,160); const Scalar GREEN = Scalar(0,255,0); const int BGD_KEY = CV_EVENT_FLAG_CTRLKEY; //Ctrl鍵 const int FGD_KEY = CV_EVENT_FLAG_SHIFTKEY; //Shift鍵 static void getBinMask( const Mat& comMask, Mat& binMask ) { if( comMask.empty() || comMask.type()!=CV_8UC1 ) CV_Error( CV_StsBadArg, "comMask is empty or has incorrect type (not CV_8UC1)" ); if( binMask.empty() || binMask.rows!=comMask.rows || binMask.cols!=comMask.cols ) binMask.create( comMask.size(), CV_8UC1 ); binMask = comMask & 1; //得到mask的最低位,實際上是只保留確定的或者有可能的前景點當做mask } class GCApplication { public: enum{ NOT_SET = 0, IN_PROCESS = 1, SET = 2 }; static const int radius = 2; static const int thickness = -1; void reset(); void setImageAndWinName( const Mat& _image, const string& _winName ); void showImage() const; void mouseClick( int event, int x, int y, int flags, void* param ); int nextIter(); int getIterCount() const { return iterCount; } private: void setRectInMask(); void setLblsInMask( int flags, Point p, bool isPr ); const string* winName; const Mat* image; Mat mask; Mat bgdModel, fgdModel; uchar rectState, lblsState, prLblsState; bool isInitialized; Rect rect; vector<Point> fgdPxls, bgdPxls, prFgdPxls, prBgdPxls; int iterCount; }; /*給類的變量賦值*/ void GCApplication::reset() { if( !mask.empty() ) mask.setTo(Scalar::all(GC_BGD)); bgdPxls.clear(); fgdPxls.clear(); prBgdPxls.clear(); prFgdPxls.clear(); isInitialized = false; rectState = NOT_SET; //NOT_SET == 0 lblsState = NOT_SET; prLblsState = NOT_SET; iterCount = 0; } /*給類的成員變量賦值而已*/ void GCApplication::setImageAndWinName( const Mat& _image, const string& _winName ) { if( _image.empty() || _winName.empty() ) return; image = &_image; winName = &_winName; mask.create( image->size(), CV_8UC1); reset(); } /*顯示4個點，一個矩形和圖像內容，因為后面的步驟很多地方都要用到這個函數，所以單獨拿出來*/ void GCApplication::showImage() const { if( image->empty() || winName->empty() ) return; Mat res; Mat binMask; if( !isInitialized ) image->copyTo( res ); else { getBinMask( mask, binMask ); image->copyTo( res, binMask ); //按照最低位是0還是1來復制，只保留跟前景有關的圖像，比如說可能的前景，可能的背景 } vector<Point>::const_iterator it; /*下面4句代碼是將選中的4個點用不同的顏色顯示出來*/ for( it = bgdPxls.begin(); it != bgdPxls.end(); ++it ) //迭代器可以看成是一個指針 circle( res, *it, radius, BLUE, thickness ); for( it = fgdPxls.begin(); it != fgdPxls.end(); ++it ) //確定的前景用紅色表示 circle( res, *it, radius, RED, thickness ); for( it = prBgdPxls.begin(); it != prBgdPxls.end(); ++it ) circle( res, *it, radius, LIGHTBLUE, thickness ); for( it = prFgdPxls.begin(); it != prFgdPxls.end(); ++it ) circle( res, *it, radius, PINK, thickness ); /*畫矩形*/ if( rectState == IN_PROCESS || rectState == SET ) rectangle( res, Point( rect.x, rect.y ), Point(rect.x + rect.width, rect.y + rect.height ), GREEN, 2); imshow( *winName, res ); } /*該步驟完成后，mask圖像中rect內部是3，外面全是0*/ void GCApplication::setRectInMask() { assert( !mask.empty() ); mask.setTo( GC_BGD ); //GC_BGD == 0 rect.x = max(0, rect.x); rect.y = max(0, rect.y); rect.width = min(rect.width, image->cols-rect.x); rect.height = min(rect.height, image->rows-rect.y); (mask(rect)).setTo( Scalar(GC_PR_FGD) ); //GC_PR_FGD == 3，矩形內部,為可能的前景點 } void GCApplication::setLblsInMask( int flags, Point p, bool isPr ) { vector<Point> *bpxls, *fpxls; uchar bvalue, fvalue; if( !isPr ) //確定的點 { bpxls = &bgdPxls; fpxls = &fgdPxls; bvalue = GC_BGD; //0 fvalue = GC_FGD; //1 } else //概率點 { bpxls = &prBgdPxls; fpxls = &prFgdPxls; bvalue = GC_PR_BGD; //2 fvalue = GC_PR_FGD; //3 } if( flags & BGD_KEY ) { bpxls->push_back(p); circle( mask, p, radius, bvalue, thickness ); //該點處為2 } if( flags & FGD_KEY ) { fpxls->push_back(p); circle( mask, p, radius, fvalue, thickness ); //該點處為3 } } /*鼠標響應函數，參數flags為CV_EVENT_FLAG的組合*/ void GCApplication::mouseClick( int event, int x, int y, int flags, void* ) { // TODO add bad args check switch( event ) { case CV_EVENT_LBUTTONDOWN: // set rect or GC_BGD(GC_FGD) labels { bool isb = (flags & BGD_KEY) != 0, isf = (flags & FGD_KEY) != 0; if( rectState == NOT_SET && !isb && !isf )//只有左鍵按下時 { rectState = IN_PROCESS; //表示正在畫矩形 rect = Rect( x, y, 1, 1 ); } if ( (isb || isf) && rectState == SET ) //按下了alt鍵或者shift鍵，且畫好了矩形，表示正在畫前景背景點 lblsState = IN_PROCESS; } break; case CV_EVENT_RBUTTONDOWN: // set GC_PR_BGD(GC_PR_FGD) labels { bool isb = (flags & BGD_KEY) != 0, isf = (flags & FGD_KEY) != 0; if ( (isb || isf) && rectState == SET ) //正在畫可能的前景背景點 prLblsState = IN_PROCESS; } break; case CV_EVENT_LBUTTONUP: if( rectState == IN_PROCESS ) { rect = Rect( Point(rect.x, rect.y), Point(x,y) ); //矩形結束 rectState = SET; setRectInMask(); assert( bgdPxls.empty() && fgdPxls.empty() && prBgdPxls.empty() && prFgdPxls.empty() ); showImage(); } if( lblsState == IN_PROCESS ) //已畫了前后景點 { setLblsInMask(flags, Point(x,y), false); //畫出前景點 lblsState = SET; showImage(); } break; case CV_EVENT_RBUTTONUP: if( prLblsState == IN_PROCESS ) { setLblsInMask(flags, Point(x,y), true); //畫出背景點 prLblsState = SET; showImage(); } break; case CV_EVENT_MOUSEMOVE: if( rectState == IN_PROCESS ) { rect = Rect( Point(rect.x, rect.y), Point(x,y) ); assert( bgdPxls.empty() && fgdPxls.empty() && prBgdPxls.empty() && prFgdPxls.empty() ); showImage(); //不斷的顯示圖片 } else if( lblsState == IN_PROCESS ) { setLblsInMask(flags, Point(x,y), false); showImage(); } else if( prLblsState == IN_PROCESS ) { setLblsInMask(flags, Point(x,y), true); showImage(); } break; } } /*該函數進行grabcut算法，并且返回算法運行迭代的次數*/ int GCApplication::nextIter() { if( isInitialized ) //使用grab算法進行一次迭代，參數2為mask，里面存的mask位是：矩形內部除掉那些可能是背景或者已經確定是背景后的所有的點，且mask同時也為輸出 //保存的是分割后的前景圖像 grabCut( *image, mask, rect, bgdModel, fgdModel, 1 ); else { if( rectState != SET ) return iterCount; if( lblsState == SET || prLblsState == SET ) grabCut( *image, mask, rect, bgdModel, fgdModel, 1, GC_INIT_WITH_MASK ); else grabCut( *image, mask, rect, bgdModel, fgdModel, 1, GC_INIT_WITH_RECT ); isInitialized = true; } iterCount++; bgdPxls.clear(); fgdPxls.clear(); prBgdPxls.clear(); prFgdPxls.clear(); return iterCount; } GCApplication gcapp; static void on_mouse( int event, int x, int y, int flags, void* param ) { gcapp.mouseClick( event, x, y, flags, param ); } int main( int argc, char** argv ) { string filename; cout<<" Grabcuts ! \n"; cout<<"input image name: "<<endl; cin>>filename; Mat image = imread( filename, 1 ); if( image.empty() ) { cout << "\n Durn, couldn't read image filename " << filename << endl; return 1; } help(); const string winName = "image"; cvNamedWindow( winName.c_str(), CV_WINDOW_AUTOSIZE ); cvSetMouseCallback( winName.c_str(), on_mouse, 0 ); gcapp.setImageAndWinName( image, winName ); gcapp.showImage(); for(;;) { int c = cvWaitKey(0); switch( (char) c ) { case '\x1b': cout << "Exiting ..." << endl; goto exit_main; case 'r': cout << endl; gcapp.reset(); gcapp.showImage(); break; case 'n': ComputeTime ct ; ct.Begin(); int iterCount = gcapp.getIterCount(); cout << "<" << iterCount << "... "; int newIterCount = gcapp.nextIter(); if( newIterCount > iterCount ) { gcapp.showImage(); cout << iterCount << ">" << endl; cout<<"運行時間: "<<ct.End()<<endl; } else cout << "rect must be determined>" << endl; break; } } exit_main: cvDestroyWindow( winName.c_str() ); return 0; }

lazy snapping

lszySnapping.cpp

LazySnapping.cpp#include "stdafx.h" #include <cv.h> #include <highgui.h> #include "graph.h" #include <vector> #include <iostream> #include <cmath> #include <string> using namespace std; typedef Graph<float,float,float> GraphType; class LasySnapping { public : LasySnapping(); ~LasySnapping() { if(graph) { delete graph; } }; private : vector<CvPoint> forePts; vector<CvPoint> backPts; IplImage* image; // average color of foreground points unsigned char avgForeColor[3]; // average color of background points unsigned char avgBackColor[3]; public : void setImage(IplImage* image) { this->image = image; graph = new GraphType(image->width*image->height,image->width*image->height*2); } // include-pen locus void setForegroundPoints(vector<CvPoint> pts) { forePts.clear(); for(int i =0; i< pts.size(); i++) { if(!isPtInVector(pts[i],forePts)) { forePts.push_back(pts[i]); } } if(forePts.size() == 0) { return; } int sum[3] = {0}; for(int i =0; i < forePts.size(); i++) { unsigned char* p = (unsigned char*)image->imageData + forePts[i].x * 3 + forePts[i].y*image->widthStep; sum[0] += p[0]; sum[1] += p[1]; sum[2] += p[2]; } cout<<sum[0]<<" " <<forePts.size()<<endl; avgForeColor[0] = sum[0]/forePts.size(); avgForeColor[1] = sum[1]/forePts.size(); avgForeColor[2] = sum[2]/forePts.size(); } // exclude-pen locus void setBackgroundPoints(vector<CvPoint> pts) { backPts.clear(); for(int i =0; i< pts.size(); i++) { if(!isPtInVector(pts[i],backPts)) { backPts.push_back(pts[i]); } } if(backPts.size() == 0) { return; } int sum[3] = {0}; for(int i =0; i < backPts.size(); i++) { unsigned char* p = (unsigned char*)image->imageData + backPts[i].x * 3 + backPts[i].y*image->widthStep; sum[0] += p[0]; sum[1] += p[1]; sum[2] += p[2]; } avgBackColor[0] = sum[0]/backPts.size(); avgBackColor[1] = sum[1]/backPts.size(); avgBackColor[2] = sum[2]/backPts.size(); } // return maxflow of graph int runMaxflow(); // get result, a grayscale mast image indicating forground by 255 and background by 0 IplImage* getImageMask(); private : float colorDistance(unsigned char* color1, unsigned char* color2); float minDistance(unsigned char* color, vector<CvPoint> points); bool isPtInVector(CvPoint pt, vector<CvPoint> points); void getE1(unsigned char* color,float* energy); float getE2(unsigned char* color1,unsigned char* color2); GraphType *graph; }; LasySnapping::LasySnapping() { graph = NULL; avgForeColor[0] = 0; avgForeColor[1] = 0; avgForeColor[2] = 0; avgBackColor[0] = 0; avgBackColor[1] = 0; avgBackColor[2] = 0; } float LasySnapping::colorDistance(unsigned char* color1, unsigned char* color2) { return sqrt(((float)color1[0]-(float)color2[0])*((float)color1[0]-(float)color2[0])+ ((float)color1[1]-(float)color2[1])*((float)color1[1]-(float)color2[1])+ ((float)color1[2]-(float)color2[2])*((float)color1[2]-(float)color2[2])); } float LasySnapping::minDistance(unsigned char* color, vector<CvPoint> points) { float distance = -1; for(int i =0 ; i < points.size(); i++) { unsigned char* p = (unsigned char*)image->imageData + points[i].y * image->widthStep + points[i].x * image->nChannels; float d = colorDistance(p,color); if(distance < 0 ) { distance = d; } else { if(distance > d) { distance = d; } } } return distance; } bool LasySnapping::isPtInVector(CvPoint pt, vector<CvPoint> points) { for(int i =0 ; i < points.size(); i++) { if(pt.x == points[i].x && pt.y == points[i].y) { return true; } } return false; } void LasySnapping::getE1(unsigned char* color,float* energy) { // average distance float df = colorDistance(color,avgForeColor); float db = colorDistance(color,avgBackColor); // min distance from background points and forground points // float df = minDistance(color,forePts); // float db = minDistance(color,backPts); energy[0] = df/(db+df); energy[1] = db/(db+df); } float LasySnapping::getE2(unsigned char* color1,unsigned char* color2) { const float EPSILON = 0.01; float lambda = 100; return lambda/(EPSILON+ (color1[0]-color2[0])*(color1[0]-color2[0])+ (color1[1]-color2[1])*(color1[1]-color2[1])+ (color1[2]-color2[2])*(color1[2]-color2[2])); } int LasySnapping::runMaxflow() { const float INFINNITE_MAX = 1e10; int indexPt = 0; for(int h = 0; h < image->height; h ++) { unsigned char* p = (unsigned char*)image->imageData + h *image->widthStep; for(int w = 0; w < image->width; w ++) { // calculate energe E1 float e1[2]={0}; if(isPtInVector(cvPoint(w,h),forePts)) { e1[0] =0; e1[1] = INFINNITE_MAX; } else if (isPtInVector(cvPoint(w,h),backPts)) { e1[0] = INFINNITE_MAX; e1[1] = 0; } else { getE1(p,e1); } // add node graph->add_node(); graph->add_tweights(indexPt, e1[0],e1[1]); // add edge, 4-connect if(h > 0 && w > 0) { float e2 = getE2(p,p-3); graph->add_edge(indexPt,indexPt-1,e2,e2); e2 = getE2(p,p-image->widthStep); graph->add_edge(indexPt,indexPt-image->width,e2,e2); } p+= 3; indexPt ++; } } return graph->maxflow(); } IplImage* LasySnapping::getImageMask() { IplImage* gray = cvCreateImage(cvGetSize(image),8,1); int indexPt =0; for(int h =0; h < image->height; h++) { unsigned char* p = (unsigned char*)gray->imageData + h*gray->widthStep; for(int w =0 ;w <image->width; w++) { if (graph->what_segment(indexPt) == GraphType::SOURCE) { *p = 0; } else { *p = 255; } p++; indexPt ++; } } return gray; } // global vector<CvPoint> forePts; vector<CvPoint> backPts; int currentMode = 0;// indicate foreground or background, foreground as default CvScalar paintColor[2] = {CV_RGB(0,0,255),CV_RGB(255,0,0)}; IplImage* image = NULL; char* winName = "lazySnapping"; IplImage* imageDraw = NULL; const int SCALE = 4; void on_mouse( int event, int x, int y, int flags, void* ) { if( event == CV_EVENT_LBUTTONUP ) { if(backPts.size() == 0 && forePts.size() == 0) { return; } LasySnapping ls; IplImage* imageLS = cvCreateImage(cvSize(image->width/SCALE,image->height/SCALE), 8,3); cvResize(image,imageLS); ls.setImage(imageLS); ls.setBackgroundPoints(backPts); ls.setForegroundPoints(forePts); ls.runMaxflow(); IplImage* mask = ls.getImageMask(); IplImage* gray = cvCreateImage(cvGetSize(image),8,1); cvResize(mask,gray); // edge cvCanny(gray,gray,50,150,3); IplImage* showImg = cvCloneImage(imageDraw); for(int h =0; h < image->height; h ++) { unsigned char* pgray = (unsigned char*)gray->imageData + gray->widthStep*h; unsigned char* pimage = (unsigned char*)showImg->imageData + showImg->widthStep*h; for(int width =0; width < image->width; width++) { if(*pgray++ != 0 ) { pimage[0] = 0; pimage[1] = 255; pimage[2] = 0; } pimage+=3; } } cvSaveImage("t.bmp",showImg); cvShowImage(winName,showImg); cvReleaseImage(&imageLS); cvReleaseImage(&mask); cvReleaseImage(&showImg); cvReleaseImage(&gray); } else if( event == CV_EVENT_LBUTTONDOWN ) { } else if( event == CV_EVENT_MOUSEMOVE && (flags & CV_EVENT_FLAG_LBUTTON)) { CvPoint pt = cvPoint(x,y); if(currentMode == 0) {//foreground forePts.push_back(cvPoint(x/SCALE,y/SCALE)); } else {//background backPts.push_back(cvPoint(x/SCALE,y/SCALE)); } cvCircle(imageDraw,pt,2,paintColor[currentMode]); cvShowImage(winName,imageDraw); } } int main(int argc, char** argv) { //if(argc != 2) //{ // cout<<"command : lazysnapping inputImage"<<endl; // return 0; // } string image_name; cout<<"input image name: "<<endl; cin>>image_name; cvNamedWindow(winName,1); cvSetMouseCallback( winName, on_mouse, 0); image = cvLoadImage(image_name.c_str(),CV_LOAD_IMAGE_COLOR); imageDraw = cvCloneImage(image); cvShowImage(winName, image); for(;;) { int c = cvWaitKey(0); c = (char)c; if(c == 27) {//exit break; } else if(c == 'r') {//reset image = cvLoadImage(image_name.c_str(),CV_LOAD_IMAGE_COLOR); imageDraw = cvCloneImage(image); forePts.clear(); backPts.clear(); currentMode = 0; cvShowImage(winName, image); } else if(c == 'b') {//change to background selection currentMode = 1; }else if(c == 'f') {//change to foreground selection currentMode = 0; } } cvReleaseImage(&image); cvReleaseImage(&imageDraw); return 0; }

由漢字生成圖片

AddChinese.cpp

#include "stdafx.h" #include <opencv2/core/core.hpp> #include <opencv2/highgui/highgui.hpp> #include "CvxText.h" #pragma comment(lib,"freetype255d.lib") #pragma comment(lib,"opencv_core2410d.lib") #pragma comment(lib,"opencv_highgui2410d.lib") #pragma comment(lib,"opencv_imgproc2410d.lib") using namespace std; using namespace cv; #define ROW_BLOCK 2 #define COLUMN_Block 2 writePng.cpp : 定義控制臺應用程序的入口點。 int run_test_png(Mat &mat,string image_name) { /*采用自己設置的參數來保存圖片*/ //Mat mat(480, 640, CV_8UC4); //createAlphaMat(mat); vector<int> compression_params; compression_params.push_back(CV_IMWRITE_PNG_COMPRESSION); compression_params.push_back(9); //png格式下，默認的參數為3. try { imwrite(image_name, mat, compression_params); } catch (runtime_error& ex) { fprintf(stderr, "Exception converting image to PNG format: %s\n", ex.what()); return 1; } fprintf(stdout, "Saved PNG file with alpha data.\n"); waitKey(0); return 0; } int coloured(Mat &template_src, Mat &mat_png, CvScalar color) { for (int i = 0; i < template_src.rows; ++i) { for (int j = 0; j < template_src.cols; ++j) { Vec4b& bgra = mat_png.at<Vec4b>(i, j); //int temp = template_src.at<uchar>(i,j); if (template_src.at<uchar>(i,j)== 0) { bgra[0] = color.val[0]; //b通道 bgra[1] = color.val[1]; //g通道 bgra[2] = color.val[2]; //r通道 bgra[3] = 255;//alpha通道全部設置為透明完全透明為0，否則為255 } else { bgra[3] = 0;//alpha通道全部設置為透明完全透明為0，否則為255 } } } return 0; } void ImageBinarization(IplImage *src) { /*對灰度圖像二值化，自適應門限threshold*/ int i,j,width,height,step,chanel,threshold; /*size是圖像尺寸，svg是灰度直方圖均值，va是方差*/ float size,avg,va,maxVa,p,a,s; unsigned char *dataSrc; float histogram[256]; width = src->width; height = src->height; dataSrc = (unsigned char *)src->imageData; step = src->widthStep/sizeof(char); chanel = src->nChannels; /*計算直方圖并歸一化histogram*/ for(i=0; i<256; i++) histogram[i] = 0; for(i=0; i<height; i++) for(j=0; j<width*chanel; j++) { histogram[dataSrc[i*step+j]-'0'+48]++; } size = width * height; for(i=0; i<256; i++) histogram[i] /=size; /*計算灰度直方圖中值和方差*/ avg = 0; for(i=0; i<256; i++) avg += i*histogram[i]; va = 0; for(i=0; i<256; i++) va += fabs(i*i*histogram[i]-avg*avg); /*利用加權最大方差求門限*/ threshold = 20; maxVa = 0; p = a = s = 0; for(i=0; i<256; i++) { p += histogram[i]; a += i*histogram[i]; s = (avg*p-a)*(avg*p-a)/p/(1-p); if(s > maxVa) { threshold = i; maxVa = s; } } /*二值化*/ for(i=0; i<height; i++) for(j=0; j<width*chanel; j++) { if(dataSrc[i*step+j] > threshold) dataSrc[i*step+j] = 255; else dataSrc[i*step+j] = 0; } } Mat binaryzation(Mat &src) { Mat des_gray(src.size(),CV_8UC1); cvtColor(src,des_gray,CV_BGR2GRAY); //Mat bin_mat(); IplImage temp(des_gray); ImageBinarization(&temp); //threshold(des_gray,des_gray,150,255,THRESH_BINARY); imshow("二值圖像",des_gray); return des_gray; } int generate_chinese(const int size_zi, const char *msg ,int number,CvScalar color) { //int size_zi = 50;//字體大小 CvSize czSize; //目標圖像尺寸 float p = 0.5; CvScalar fsize; //讀取TTF字體文件 CvxText text("simhei.ttf"); //設置字體屬性 字體大小/空白比例/間隔比例/旋轉角度 fsize = cvScalar(size_zi, 1, 0.1, 0); text.setFont(NULL, &fsize, NULL, &p); czSize.width = size_zi*number; czSize.height = size_zi; //加載原圖像 IplImage* ImageSrc = cvCreateImage(czSize,IPL_DEPTH_8U,3);//cvLoadImage(Imagename, CV_LOAD_IMAGE_UNCHANGED); //Mat image(ImageSrc); //createAlphaMat(image); //ImageSrc = ? //IplImage temp(image); //ImageSrc = &temp; //設置原圖像文字 text.putText(ImageSrc, msg, cvPoint(1, size_zi), color); //顯示原圖像 cvShowImage("原圖", ImageSrc); string hanzi = msg; hanzi = hanzi + ".png"; Mat chinese(ImageSrc,true); Mat gray = binaryzation(chinese); imwrite("chinese_gray.jpg",gray); Mat mat_png(chinese.size(),CV_8UC4); coloured(gray,mat_png,color); run_test_png(mat_png,hanzi); // cvSaveImage("hanzi.jpg",reDstImage); //run_test_png(chinese,hanzi); //等待按鍵事件 cvWaitKey(); return 0; } int main() { CvScalar color = CV_RGB(0,0,0); int size = 200; const char* msg = "你好a";//暫時一行字不要太長 int number = 3;//字符個數 generate_chinese(size,msg,number,color); return 0; }

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