OpenCV官网:https://opencv.org/
OpenCV是一个基于BSD许可(开源)发行的跨平台计算机视觉库,可以运行在Linux、Windows、Android和Mac OS操作系统上。它轻量级而且高效——由一系列 C 函数和少量 C++ 类构成,同时提供了Python、Ruby、MATLAB等语言的接口,实现了图像处理和计算机视觉方面的很多通用算法。
OpenCV用C++语言编写,它的主要接口也是C++语言,但是依然保留了大量的C语言接口。该库也有大量的Python、Java and MATLAB/OCTAVE(版本2.5)的接口。这些语言的API接口函数可以通过在线文档获得。如今也提供对于C#、Ch、Ruby的支持。所有新的开发和算法都是用C++接口。一个使用CUDA的GPU接口也于2010年9月开始实现。
下面转载几个OpenCV的程序。
我的环境:
$ pkg-config --modversion opencv 2.4.13 $ uname -a Linux toa 3.10.0-693.17.1.el7.x86_64 #1 SMP Thu Jan 25 20:13:58 UTC 2018 x86_64 x86_64 x86_64 GNU/Linux $ g++ --version g++ (GCC) 4.8.5 20150623 (Red Hat 4.8.5-16)
1.显示图片https://www.cnblogs.com/Crysaty/p/6638152.html
#include <highgui.h> int main(int argc,char ** argv) { IplImage* img = cvLoadImage(argv[1],CV_LOAD_IMAGE_COLOR); cvNamedWindow("Image_show",CV_WINDOW_AUTOSIZE); cvShowImage("Image_show",img); cvWaitKey(0); cvReleaseImage(&img); cvDestroyWindow("Image_show"); return 0; }
编译运行:
$ make gcc main.c `pkg-config --cflags --libs opencv` $ ./a.out ../windows.png
效果图(左),原图(右):
一个C++的代码:
#include <opencv2/opencv.hpp> #include <iostream> using namespace std; using namespace cv; int main(int argc, char **argv) { Mat imggray=imread(argv[1],CV_LOAD_IMAGE_COLOR); cvtColor(imggray,imggray,CV_RGB2GRAY);//RGB2GRAY imshow("123",imggray);//显示图片 waitKey(0); return 1; }
编译与运行:
$ make g++ main.c `pkg-config --cflags --libs opencv` $ ./a.out ../wongrgb.jpg
2.二值图+轮廓图https://www.cnblogs.com/always-chang/p/6170859.html
#include <opencv2/opencv.hpp> using namespace std; #pragma comment(linker, "/subsystem:\"windows\" /entry:\"mainCRTStartup\"") IplImage *g_pGrayImage = NULL; const char *pstrWindowsBinaryTitle = "二值图"; const char *pstrWindowsOutLineTitle = "轮廓图"; CvSeq *g_pcvSeq = NULL; void on_trackbar(int pos) { // 转为二值图 IplImage *pBinaryImage = cvCreateImage(cvGetSize(g_pGrayImage), IPL_DEPTH_8U, 1); cvThreshold(g_pGrayImage, pBinaryImage, pos, 255, CV_THRESH_BINARY); // 显示二值图 cvShowImage(pstrWindowsBinaryTitle, pBinaryImage); CvMemStorage* cvMStorage = cvCreateMemStorage(); // 检索轮廓并返回检测到的轮廓的个数 cvFindContours(pBinaryImage, cvMStorage, &g_pcvSeq); IplImage *pOutlineImage = cvCreateImage(cvGetSize(g_pGrayImage), IPL_DEPTH_8U, 3); int _levels = 5; cvZero(pOutlineImage); cvDrawContours(pOutlineImage, g_pcvSeq, CV_RGB(255, 0, 0), CV_RGB(0, 255, 0), _levels); cvShowImage(pstrWindowsOutLineTitle, pOutlineImage); cvReleaseMemStorage(&cvMStorage); cvReleaseImage(&pBinaryImage); cvReleaseImage(&pOutlineImage); } int main(int argc, char** argv) { const char *pstrWindowsSrcTitle = "原图"; const char *pstrWindowsToolBarName = "二值化"; // 从文件中加载原图 IplImage *pSrcImage = cvLoadImage(argv[1], CV_LOAD_IMAGE_UNCHANGED); // 显示原图 cvNamedWindow(pstrWindowsSrcTitle, CV_WINDOW_AUTOSIZE); cvShowImage(pstrWindowsSrcTitle, pSrcImage); // 转为灰度图 g_pGrayImage = cvCreateImage(cvGetSize(pSrcImage), IPL_DEPTH_8U, 1); cvCvtColor(pSrcImage, g_pGrayImage, CV_BGR2GRAY); // 创建二值图和轮廓图窗口 cvNamedWindow(pstrWindowsBinaryTitle, CV_WINDOW_AUTOSIZE); cvNamedWindow(pstrWindowsOutLineTitle, CV_WINDOW_AUTOSIZE); // 滑动条 int nThreshold = 0; cvCreateTrackbar(pstrWindowsToolBarName, pstrWindowsBinaryTitle, &nThreshold, 254, on_trackbar); on_trackbar(1); cvWaitKey(0); cvDestroyWindow(pstrWindowsSrcTitle); cvDestroyWindow(pstrWindowsBinaryTitle); cvDestroyWindow(pstrWindowsOutLineTitle); cvReleaseImage(&pSrcImage); cvReleaseImage(&g_pGrayImage); return 0; }
编译与运行:
$ make g++ main.c `pkg-config --cflags --libs opencv` $ ./a.out ../wong.jpg
效果图:
3.鼠标绘图https://www.cnblogs.com/always-chang/p/6170859.html
#include <opencv2/opencv.hpp> using namespace std; #pragma comment(linker, "/subsystem:\"windows\" /entry:\"mainCRTStartup\"") const char *pstrWindowsMouseDrawTitle = "鼠标绘图"; // 鼠标消息的回调函数 void on_mouse(int event, int x, int y, int flags, void* param) { static bool s_bMouseLButtonDown = false; static CvPoint s_cvPrePoint = cvPoint(0, 0); switch (event) { case CV_EVENT_LBUTTONDOWN: s_bMouseLButtonDown = true; s_cvPrePoint = cvPoint(x, y); break; case CV_EVENT_LBUTTONUP: s_bMouseLButtonDown = false; break; case CV_EVENT_MOUSEMOVE: if (s_bMouseLButtonDown) { CvPoint cvCurrPoint = cvPoint(x, y); cvLine((IplImage*)param, s_cvPrePoint, cvCurrPoint, CV_RGB(0, 0, 20), 3); s_cvPrePoint = cvCurrPoint; cvShowImage(pstrWindowsMouseDrawTitle, (IplImage*)param); } break; } } int main() { const int MAX_WIDTH = 500, MAX_HEIGHT = 400; const char *pstrSaveImageName = "Draw.jpg"; IplImage *pSrcImage = cvCreateImage(cvSize(MAX_WIDTH, MAX_HEIGHT), IPL_DEPTH_8U, 3); cvSet(pSrcImage, CV_RGB(255, 255, 255)); //可以用cvSet()将图像填充成白色 cvNamedWindow(pstrWindowsMouseDrawTitle, CV_WINDOW_AUTOSIZE); cvShowImage(pstrWindowsMouseDrawTitle, pSrcImage); cvSetMouseCallback(pstrWindowsMouseDrawTitle, on_mouse, (void*)pSrcImage); int c; do{ c = cvWaitKey(0); switch ((char)c) { case 'r'://r重画 cvSet(pSrcImage, CV_RGB(255, 255, 255)); cvShowImage(pstrWindowsMouseDrawTitle, pSrcImage); break; case 's'://s保存图像 cvSaveImage(pstrSaveImageName, pSrcImage); break; } } while (c > 0 && c != 27); cvDestroyWindow(pstrWindowsMouseDrawTitle); cvReleaseImage(&pSrcImage); return 0; }
编译与运行:
$ make g++ main.c `pkg-config --cflags --libs opencv` $ ./a.out
效果图:
4.灰度直方图https://www.cnblogs.com/always-chang/p/6170859.html
#include <opencv2/opencv.hpp> #include <opencv2/legacy/compat.hpp> using namespace std; #pragma comment(linker, "/subsystem:\"windows\" /entry:\"mainCRTStartup\"") void FillWhite(IplImage *pImage) { cvRectangle(pImage, cvPoint(0, 0), cvPoint(pImage->width, pImage->height), CV_RGB(255, 255, 255), CV_FILLED); } // 创建灰度图像的直方图 CvHistogram* CreateGrayImageHist(IplImage **ppImage) { int nHistSize = 256; float fRange[] = { 0, 255 }; //灰度级的范围 float *pfRanges[] = { fRange }; CvHistogram *pcvHistogram = cvCreateHist(1, &nHistSize, CV_HIST_ARRAY, pfRanges); cvCalcHist(ppImage, pcvHistogram); return pcvHistogram; } // 根据直方图创建直方图图像 IplImage* CreateHisogramImage(int nImageWidth, int nScale, int nImageHeight, CvHistogram *pcvHistogram) { IplImage *pHistImage = cvCreateImage(cvSize(nImageWidth * nScale, nImageHeight), IPL_DEPTH_8U, 1); FillWhite(pHistImage); //统计直方图中的最大直方块 float fMaxHistValue = 0; cvGetMinMaxHistValue(pcvHistogram, NULL, &fMaxHistValue, NULL, NULL); //分别将每个直方块的值绘制到图中 int i; for (i = 0; i < nImageWidth; i++) { float fHistValue = cvQueryHistValue_1D(pcvHistogram, i); //像素为i的直方块大小 int nRealHeight = cvRound((fHistValue / fMaxHistValue) * nImageHeight); //要绘制的高度 cvRectangle(pHistImage, cvPoint(i * nScale, nImageHeight - 1), cvPoint((i + 1) * nScale - 1, nImageHeight - nRealHeight), cvScalar(i, 0, 0, 0), CV_FILLED ); } return pHistImage; } int main(int argc, char** argv) { const char *pstrWindowsSrcTitle = "原图"; const char *pstrWindowsGrayTitle = "灰度图"; const char *pstrWindowsHistTitle = "直方图"; // 从文件中加载原图 IplImage *pSrcImage = cvLoadImage(argv[1], CV_LOAD_IMAGE_UNCHANGED); IplImage *pGrayImage = cvCreateImage(cvGetSize(pSrcImage), IPL_DEPTH_8U, 1); // 灰度图 cvCvtColor(pSrcImage, pGrayImage, CV_BGR2GRAY); // 灰度直方图 CvHistogram *pcvHistogram = CreateGrayImageHist(&pGrayImage); // 创建直方图图像 int nHistImageWidth = 255; int nHistImageHeight = 150; //直方图图像高度 int nScale = 2; IplImage *pHistImage = CreateHisogramImage(nHistImageWidth, nScale, nHistImageHeight, pcvHistogram); // 显示 cvNamedWindow(pstrWindowsSrcTitle, CV_WINDOW_AUTOSIZE); cvNamedWindow(pstrWindowsGrayTitle, CV_WINDOW_AUTOSIZE); cvNamedWindow(pstrWindowsHistTitle, CV_WINDOW_AUTOSIZE); cvShowImage(pstrWindowsSrcTitle, pSrcImage); cvShowImage(pstrWindowsGrayTitle, pGrayImage); cvShowImage(pstrWindowsHistTitle, pHistImage); cvWaitKey(0); cvReleaseHist(&pcvHistogram); cvDestroyWindow(pstrWindowsSrcTitle); cvDestroyWindow(pstrWindowsGrayTitle); cvDestroyWindow(pstrWindowsHistTitle); cvReleaseImage(&pSrcImage); cvReleaseImage(&pGrayImage); cvReleaseImage(&pHistImage); return 0; }
编译与运行:
$ make g++ main.c `pkg-config --cflags --libs opencv` $ ./a.out ../wongrgb.jpg
效果图:
5.灰度直方图均衡化
#include <opencv2/opencv.hpp> #include <opencv2/legacy/compat.hpp> using namespace std; #pragma comment(linker, "/subsystem:\"windows\" /entry:\"mainCRTStartup\"") void FillWhite(IplImage *pImage) { cvRectangle(pImage, cvPoint(0, 0), cvPoint(pImage->width, pImage->height), CV_RGB(255, 255, 255), CV_FILLED); } // 创建灰度图像的直方图 CvHistogram* CreateGrayImageHist(IplImage **ppImage) { int nHistSize = 256; float fRange[] = { 0, 255 }; //灰度级的范围 float *pfRanges[] = { fRange }; CvHistogram *pcvHistogram = cvCreateHist(1, &nHistSize, CV_HIST_ARRAY, pfRanges); cvCalcHist(ppImage, pcvHistogram); return pcvHistogram; } // 根据直方图创建直方图图像 IplImage* CreateHisogramImage(int nImageWidth, int nScale, int nImageHeight, CvHistogram *pcvHistogram) { IplImage *pHistImage = cvCreateImage(cvSize(nImageWidth * nScale, nImageHeight), IPL_DEPTH_8U, 1); FillWhite(pHistImage); //统计直方图中的最大直方块 float fMaxHistValue = 0; cvGetMinMaxHistValue(pcvHistogram, NULL, &fMaxHistValue, NULL, NULL); //分别将每个直方块的值绘制到图中 int i; for (i = 0; i < nImageWidth; i++) { float fHistValue = cvQueryHistValue_1D(pcvHistogram, i); //像素为i的直方块大小 int nRealHeight = cvRound((fHistValue / fMaxHistValue) * nImageHeight); //要绘制的高度 cvRectangle(pHistImage, cvPoint(i * nScale, nImageHeight - 1), cvPoint((i + 1) * nScale - 1, nImageHeight - nRealHeight), cvScalar(i, 0, 0, 0), CV_FILLED ); } return pHistImage; } int main(int argc, char** argv) { const char *pstrWindowsSrcTitle = "原图"; const char *pstrWindowsGrayTitle = "灰度图"; const char *pstrWindowsHistTitle = "直方图"; const char *pstrWindowsGrayEqualizeTitle = "灰度图-均衡化后"; const char *pstrWindowsHistEqualizeTitle = "直方图-均衡化后"; // 从文件中加载原图 IplImage *pSrcImage = cvLoadImage(argv[1], CV_LOAD_IMAGE_UNCHANGED); IplImage *pGrayImage = cvCreateImage(cvGetSize(pSrcImage), IPL_DEPTH_8U, 1); IplImage *pGrayEqualizeImage = cvCreateImage(cvGetSize(pSrcImage), IPL_DEPTH_8U, 1); // 灰度图 cvCvtColor(pSrcImage, pGrayImage, CV_BGR2GRAY); // 直方图图像数据 int nHistImageWidth = 255; int nHistImageHeight = 150; int nScale = 2; // 灰度直方图及直方图图像 CvHistogram *pcvHistogram = CreateGrayImageHist(&pGrayImage); IplImage *pHistImage = CreateHisogramImage(nHistImageWidth, nScale, nHistImageHeight, pcvHistogram); // 均衡化 cvEqualizeHist(pGrayImage, pGrayEqualizeImage); // 均衡化后的灰度直方图及直方图图像 CvHistogram *pcvHistogramEqualize = CreateGrayImageHist(&pGrayEqualizeImage); IplImage *pHistEqualizeImage = CreateHisogramImage(nHistImageWidth, nScale, nHistImageHeight, pcvHistogramEqualize); // 显示 cvNamedWindow(pstrWindowsGrayTitle, CV_WINDOW_AUTOSIZE); cvNamedWindow(pstrWindowsHistTitle, CV_WINDOW_AUTOSIZE); cvNamedWindow(pstrWindowsGrayEqualizeTitle, CV_WINDOW_AUTOSIZE); cvNamedWindow(pstrWindowsHistEqualizeTitle, CV_WINDOW_AUTOSIZE); //显示代码…. cvShowImage(pstrWindowsGrayTitle, pGrayImage);//显示灰度图 cvShowImage(pstrWindowsHistTitle, pHistImage);//显示灰度直方图 cvShowImage(pstrWindowsGrayEqualizeTitle, pGrayEqualizeImage);//显示均衡化后的灰度图 cvShowImage(pstrWindowsHistEqualizeTitle, pHistEqualizeImage);//显示均衡化后的灰度直方图 //显示代码…. cvWaitKey(0); //回收资源代码… cvDestroyWindow(pstrWindowsGrayTitle); cvDestroyWindow(pstrWindowsHistTitle); cvDestroyWindow(pstrWindowsGrayEqualizeTitle); cvDestroyWindow(pstrWindowsHistEqualizeTitle); cvReleaseImage(&pSrcImage); cvReleaseImage(&pHistImage); cvReleaseImage(&pGrayEqualizeImage); cvReleaseImage(&pHistEqualizeImage); return 0; }
编译与运行:
$ make g++ main.c `pkg-config --cflags --libs opencv` $ ./a.out ../wongrgb.jpg
效果图:
6.彩色直方图均衡化
#include <opencv2/opencv.hpp> using namespace std; #pragma comment(linker, "/subsystem:\"windows\" /entry:\"mainCRTStartup\"") //彩色图像的直方图均衡化 IplImage* EqualizeHistColorImage(IplImage *pImage) { IplImage *pEquaImage = cvCreateImage(cvGetSize(pImage), pImage->depth, 3); // 原图像分成各通道后再均衡化,最后合并即彩色图像的直方图均衡化 const int MAX_CHANNEL = 4; IplImage *pImageChannel[MAX_CHANNEL] = { NULL }; int i; for (i = 0; i < pImage->nChannels; i++) pImageChannel[i] = cvCreateImage(cvGetSize(pImage), pImage->depth, 1); cvSplit(pImage, pImageChannel[0], pImageChannel[1], pImageChannel[2], pImageChannel[3]); for (i = 0; i < pImage->nChannels; i++) cvEqualizeHist(pImageChannel[i], pImageChannel[i]); cvMerge(pImageChannel[0], pImageChannel[1], pImageChannel[2], pImageChannel[3], pEquaImage); for (i = 0; i < pImage->nChannels; i++) cvReleaseImage(&pImageChannel[i]); return pEquaImage; } int main(int argc, char** argv) { const char *pstrWindowsSrcTitle = "原图"; const char *pstrWindowsHisEquaTitle = "直方图均衡化后"; // 从文件中加载原图 IplImage *pSrcImage = cvLoadImage(argv[1], CV_LOAD_IMAGE_UNCHANGED); IplImage *pHisEquaImage = EqualizeHistColorImage(pSrcImage); cvNamedWindow(pstrWindowsSrcTitle, CV_WINDOW_AUTOSIZE); cvNamedWindow(pstrWindowsHisEquaTitle, CV_WINDOW_AUTOSIZE); cvShowImage(pstrWindowsSrcTitle, pSrcImage); cvShowImage(pstrWindowsHisEquaTitle, pHisEquaImage); cvWaitKey(0); cvDestroyWindow(pstrWindowsSrcTitle); cvDestroyWindow(pstrWindowsHisEquaTitle); cvReleaseImage(&pSrcImage); cvReleaseImage(&pHisEquaImage); return 0; }
编译与运行:
$ make g++ main.c `pkg-config --cflags --libs opencv` $ ./a.out ../wongrgb.jpg
效果图(效果也不太好啊):
更多操作示例:https://blog.csdn.net/qq_35874394/article/details/53290370