Opencv函数分配图像空间:IplImage*cvCreateImage(CvSize size,int depth,int channels);size:cvSize(width,height);depth:IPL_DEPTH_8U,IPL_DEPTH_8S,IPL_DEPTH_16U,IPL_DEPTH_16S,IPL_DEPTH_32S,IPL_DEPTH_32F, IPL_DEPTH_64Fchannels:1,2,3or4.注意数据为交叉存取.彩色图像的数据编排为b0g0r0b1g1 r1...举例://分配一个单通道字节图像IplImage*img1=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,1);//分配一个三通道浮点图像IplImage*img2=cvCreateImage(cvSize(640,480),IPL_DEPTH_32F,3);释放图像空间:IplImage*img=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,1); cvReleaseImage(&img);复制图像:IplImage*img1=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,1); IplImage*img2;img2=cvCloneImage(img1);设定/获取兴趣区域:void cvSetImageROI(IplImage*image,CvRect rect);void cvResetImageROI(IplImage*image);vRect cvGetImageROI(const IplImage*image);大部分OpenCV函数都支持ROI.设定/获取兴趣通道:void cvSetImageCOI(IplImage*image,int coi);//0=allint cvGetImageCOI(const IplImage*image);大部分OpenCV函数暂不支持COI.读取存储图像从文件中载入图像:IplImage*img=0;img=cvLoadImage(fileName);if(!img)printf("Could not load image file:%s\n",fileName);Supported image formats:BMP,DIB,JPEG,JPG,JPE,PNG,PBM,PGM, PPM,SR,RAS, TIFF,TIF载入图像默认转为3通道彩色图像.如果不是，则需加flag:img=cvLoadImage(fileName,flag);flag:>0载入图像转为三通道彩色图像=0载入图像转为单通道灰度图像<0不转换载入图像(通道数与图像文件相同).图像存储为图像文件:if(!cvSaveImage(outFileName,img))printf("Could not save:%s\n",outFileName);输入文件格式由文件扩展名决定.存取图像元素假设需要读取在i行j列像点的第k通道.其中,行数i的范围为[0,height-1],列数j的范围为[0,width-1],通道k的范围为[0,nchannels-1].间接存取:(比较通用,但效率低,可读取任一类型图像数据)对单通道字节图像:CvScalar s;s=cvGet2D(img,i,j);//get the(i,j)pixel valueprintf("intensity=%f\n",s.val[0]);s.val[0]=111;cvSet2D(img,i,j,s);//set the(i,j)pixel value对多通道浮点或字节图像:IplImage*img=cvCreateImage(cvSize(640,480),IPL_DEPTH_32F,3); CvScalar s;s=cvGet2D(img,i,j);//get the(i,j)pixel valueprintf("B=%f,G=%f,R=%f\n",s.val[0],s.val[1],s.val[2]);s.val[0]=111;s.val[1]=111;s.val[2]=111;cvSet2D(img,i,j,s);//set the(i,j)pixel value直接存取:(效率高,但容易出错)对单通道字节图像:IplImage*img=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,1); ((uchar*)(img->imageData+i*img->widthStep))[j]=111;对多通道字节图像:IplImage*img=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,3); ((uchar*)(img->imageData+i*img->widthStep))[j*img->nChannels+ 0]=111;//B((uchar*)(img->imageData+i*img->widthStep))[j*img->nChannels+ 1]=112;//G((uchar*)(img->imageData+i*img->widthStep))[j*img->nChannels+ 2]=113;//R对多通道浮点图像:((float*)(img->imageData+i*img->widthStep))[j*img->nChannels+0]=111;//B((float*)(img->imageData+i*img->widthStep))[j*img->nChannels+1]=112;//G((float*)(img->imageData+i*img->widthStep))[j*img->nChannels+2]=113;//R用指针直接存取:(在某些情况下简单高效)对单通道字节图像:IplImage*img=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,1); int height=img->height;int width=img->width;int step=img->widthStep/sizeof(uchar);uchar*data=(uchar*)img->imageData;data[i*step+j]=111;对多通道字节图像:IplImage*img=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,3); int height=img->height;int width=img->width;int step=img->widthStep/sizeof(uchar);int channels=img->nChannels;uchar*data=(uchar*)img->imageData;data[i*step+j*channels+k]=111;对单通道浮点图像(假设用4字节调整):IplImage*img=cvCreateImage(cvSize(640,480),IPL_DEPTH_32F,3); int height=img->height;int width=img->width;int step=img->widthStep/sizeof(float);int channels=img->nChannels;float*data=(float*)img->imageData;data[i*step+j*channels+k]=111;使用c++wrapper进行直接存取:(简单高效)对单/多通道字节图像，多通道浮点图像定义一个c++wrapper:template<class T>class Image{private:IplImage*imgp;public:Image(IplImage*img=0){imgp=img;}~Image(){imgp=0;}void operator=(IplImage*img){imgp=img;}inline T*operator[](const int rowIndx){return((T*)(imgp->imageData+rowIndx*imgp->widthStep));} };typedef struct{unsigned char b,g,r;}RgbPixel;typedef struct{float b,g,r;}RgbPixelFloat;typedef Image<RgbPixel>RgbImage;typedef Image<RgbPixelFloat>RgbImageFloat;typedef Image<unsigned char>BwImage;typedef Image<float>BwImageFloat;单通道字节图像:IplImage*img=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,1); BwImage imgA(img);imgA[i][j]=111;多通道字节图像:IplImage*img=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,3); RgbImage imgA(img);imgA[i][j].b=111;imgA[i][j].g=111;imgA[i][j].r=111;多通道浮点图像:IplImage*img=cvCreateImage(cvSize(640,480),IPL_DEPTH_32F,3); RgbImageFloat imgA(img);imgA[i][j].b=111;imgA[i][j].g=111;imgA[i][j].r=111;图像转换转为灰度或彩色字节图像:cvConvertImage(src,dst,flags=0);src=float/byte grayscale/color imagedst=byte grayscale/color imageflags=CV_CVTIMG_FLIP(flip vertically)CV_CVTIMG_SWAP_RB(swap the R and B channels)转换彩色图像为灰度图像:使用OpenCV转换函数:cvCvtColor(cimg,gimg,CV_BGR2GRAY);//cimg->gimg直接转换:for(i=0;i<cimg->height;i++)for(j=0;j<cimg->width;j++)gimgA[i][j]=(uchar)(cimgA[i][j].b*0.114+cimgA[i][j].g*0.587+cimgA[i][j].r*0.299) ;颜色空间转换:cvCvtColor(src,dst,code);//src->dstcode=CV_<X>2<Y><X>/<Y>=RGB,BGR,GRAY,HSV,YCrCb,XYZ,Lab,Luv,HLSe.g.:CV_BGR2GRAY,CV_BGR2HSV,CV_BGR2Lab绘图命令画长方体://用宽度为1的红线在(100,100)与(200,200)之间画一长方体cvRectangle(img,cvPoint(100,100),cvPoint(200,200),cvScalar(255,0,0), 1);画圆://在(100,100)处画一半径为20的圆,使用宽度为1的绿线cvCircle(img,cvPoint(100,100),20,cvScalar(0,255,0),1);画线段://在(100,100)与(200,200)之间画绿色线段，宽度为1cvLine(img,cvPoint(100,100),cvPoint(200,200),cvScalar(0,255,0),1);画一组线段:CvPoint curve1[]={10,10,10,100,100,100,100,10};CvPoint curve2[]={30,30,30,130,130,130,130,30,150,10};CvPoint*curveArr[2]={curve1,curve2};int nCurvePts[2]={4,5};int nCurves=2;int isCurveClosed=1;int lineWidth=1;cvPolyLine(img,curveArr,nCurvePts,nCurves,isCurveClosed,cvScalar(0,25 5,255),lineWidth);画内填充色的多边形:cvFillPoly(img,curveArr,nCurvePts,nCurves,cvScalar(0,255,255));添加文本:CvFont font;double hScale=1.0;double vScale=1.0;int lineWidth=1;cvInitFont(&font,CV_FONT_HERSHEY_SIMPLEX|CV_FONT_ITALIC,hScale,vScale,0,lineWidth);cvPutText(img,"My comment",cvPoint(200,400),&font,cvScalar(255,255,0));Other possible fonts:CV_FONT_HERSHEY_SIMPLEX,CV_FONT_HERSHEY_PLAIN,CV_FONT_HERSHEY_DUPLEX,CV_FONT_HERSHEY_COMPLEX,CV_FONT_HERSHEY_TRIPLEX,CV_FONT_HERSHEY_COMPLEX_SMALL,CV_FONT_HERSHEY_SCRIPT_SIMPLEX,CV_FONT_HERSHEY_SCRIPT_COMPLEX,综述:OpenCV有针对矩阵操作的C语言函数.许多其他方法提供了更加方便的C++接口，其效率与OpenCV一样.OpenCV将向量作为1维矩阵处理.矩阵按行存储，每行有4字节的校整.分配矩阵空间:CvMat*cvCreateMat(int rows,int cols,int type);type:矩阵元素类型.格式为CV_<bit_depth>(S|U|F)C<number_of_channels>.例如:CV_8UC1表示8位无符号单通道矩阵,CV_32SC2表示32位有符号双通道矩阵.例程:CvMat*M=cvCreateMat(4,4,CV_32FC1);释放矩阵空间:CvMat*M=cvCreateMat(4,4,CV_32FC1);cvReleaseMat(&M);复制矩阵:CvMat*M1=cvCreateMat(4,4,CV_32FC1);CvMat*M2;M2=cvCloneMat(M1);初始化矩阵:double a[]={1,2,3,4,5,6,7,8,9,10,11,12};CvMat Ma=cvMat(3,4,CV_64FC1,a);另一种方法:CvMat Ma;cvInitMatHeader(&Ma,3,4,CV_64FC1,a);初始化矩阵为单位阵:CvMat*M=cvCreateMat(4,4,CV_32FC1);cvSetIdentity(M);//这里似乎有问题，不成功存取矩阵元素假设需要存取一个2维浮点矩阵的第(i,j)个元素.间接存取矩阵元素:cvmSet(M,i,j,2.0);//Set M(i,j)t=cvmGet(M,i,j);//Get M(i,j)直接存取，假设使用4-字节校正:CvMat*M=cvCreateMat(4,4,CV_32FC1);int n=M->cols;float*data=M->data.fl;data[i*n+j]=3.0;直接存取，校正字节任意:CvMat*M=cvCreateMat(4,4,CV_32FC1);int step=M->step/sizeof(float);float*data=M->data.fl;(data+i*step)[j]=3.0;直接存取一个初始化的矩阵元素:double a[16];CvMat Ma=cvMat(3,4,CV_64FC1,a);a[i*4+j]=2.0;//Ma(i,j)=2.0;矩阵/向量操作矩阵-矩阵操作:CvMat*Ma,*Mb,*Mc;cvAdd(Ma,Mb,Mc);//Ma+Mb->Mc cvSub(Ma,Mb,Mc);//Ma-Mb->Mc cvMatMul(Ma,Mb,Mc);//Ma*Mb->Mc按元素的矩阵操作:CvMat*Ma,*Mb,*Mc;cvMul(Ma,Mb,Mc);//Ma.*Mb->Mc cvDiv(Ma,Mb,Mc);//Ma./Mb->Mc cvAddS(Ma,cvScalar(-10.0),Mc);//Ma.-10->Mc向量乘积:double va[]={1,2,3};double vb[]={0,0,1};double vc[3];CvMat Va=cvMat(3,1,CV_64FC1,va);CvMat Vb=cvMat(3,1,CV_64FC1,vb);CvMat Vc=cvMat(3,1,CV_64FC1,vc);double res=cvDotProduct(&Va,&Vb);//点乘:Va.Vb->res cvCrossProduct(&Va,&Vb,&Vc);//向量积:Va x Vb->Vcend{verbatim}注意Va,Vb,Vc在向量积中向量元素个数须相同.单矩阵操作:CvMat*Ma,*Mb;cvTranspose(Ma,Mb);//transpose(Ma)->Mb(不能对自身进行转置)CvScalar t=cvTrace(Ma);//trace(Ma)->t.val[0]double d=cvDet(Ma);//det(Ma)->dcvInvert(Ma,Mb);//inv(Ma)->Mb非齐次线性系统求解:CvMat*A=cvCreateMat(3,3,CV_32FC1);CvMat*x=cvCreateMat(3,1,CV_32FC1);CvMat*b=cvCreateMat(3,1,CV_32FC1);cvSolve(&A,&b,&x);//solve(Ax=b)for x特征值分析(针对对称矩阵):CvMat*A=cvCreateMat(3,3,CV_32FC1);CvMat*E=cvCreateMat(3,3,CV_32FC1);CvMat*l=cvCreateMat(3,1,CV_32FC1);cvEigenVV(&A,&E,&l);//l=A的特征值(降序排列)//E=对应的特征向量(每行)奇异值分解SVD:CvMat*A=cvCreateMat(3,3,CV_32FC1);CvMat*U=cvCreateMat(3,3,CV_32FC1);CvMat*D=cvCreateMat(3,3,CV_32FC1);CvMat*V=cvCreateMat(3,3,CV_32FC1);cvSVD(A,D,U,V,CV_SVD_U_T|CV_SVD_V_T);//A=U D V^T 标号使得U和V返回时被转置(若没有转置标号，则有问题不成功!!!).视频序列操作从视频序列中抓取一帧OpenCV支持从摄像头或视频文件(AVI)中抓取图像.从摄像头获取初始化:CvCapture*capture=cvCaptureFromCAM(0);//capture from video device #0从视频文件获取初始化:CvCapture*capture=cvCaptureFromAVI("infile.avi");抓取帧:IplImage*img=0;if(!cvGrabFrame(capture)){//抓取一帧printf("Could not grab a frame\n\7");exit(0);}img=cvRetrieveFrame(capture);//恢复获取的帧图像要从多个摄像头同时获取图像,首先从每个摄像头抓取一帧.在抓取动作都结束后再恢复帧图像.释放抓取源:cvReleaseCapture(&capture);注意由设备抓取的图像是由capture函数自动分配和释放的.不要试图自己释放它.获取/设定帧信息获取设备特性:cvQueryFrame(capture);//this call is necessary to get correct//capture properties int frameH=(int)cvGetCaptureProperty(capture,CV_CAP_PROP_FRAME_HEIGHT);int frameW=(int)cvGetCaptureProperty(capture,CV_CAP_PROP_FRAME_WIDTH);int fps=(int)cvGetCaptureProperty(capture,CV_CAP_PROP_FPS);int numFrames=(int)cvGetCaptureProperty(capture,CV_CAP_PROP_FRAME_COUNT);所有帧数似乎只与视频文件有关.用摄像头时不对，奇怪!!!.获取帧信息:float posMsec=cvGetCaptureProperty(capture, CV_CAP_PROP_POS_MSEC);int posFrames=(int)cvGetCaptureProperty(capture,CV_CAP_PROP_POS_FRAMES);float posRatio=cvGetCaptureProperty(capture, CV_CAP_PROP_POS_AVI_RATIO);获取所抓取帧在视频序列中的位置,从首帧开始按[毫秒]算.或者从首帧开始从0标号,获取所抓取帧的标号.或者取相对位置，首帧为0，末帧为1,只对视频文件有效.设定所抓取的第一帧标号://从视频文件相对位置0.9处开始抓取cvSetCaptureProperty(capture,CV_CAP_PROP_POS_AVI_RATIO,(double)0.9);只对从视频文件抓取有效.不过似乎也不成功!!!存储视频文件初始化视频存储器:CvVideoWriter*writer=0;int isColor=1;int fps=25;//or30int frameW=640;//744for firewire camerasint frameH=480;//480for firewire cameraswriter=cvCreateVideoWriter("out.avi",CV_FOURCC('P','I','M','1'),fps,cvSize(f rameW,frameH),isColor);其他有效编码:CV_FOURCC('P','I','M','1')=MPEG-1codecCV_FOURCC('M','J','P','G')=motion-jpeg codec(does not work well)CV_FOURCC('M','P','4','2')=MPEG-4.2codecCV_FOURCC('D','I','V','3')=MPEG-4.3codecCV_FOURCC('D','I','V','X')=MPEG-4codecCV_FOURCC('U','2','6','3')=H263codecCV_FOURCC('I','2','6','3')=H263I codecCV_FOURCC('F','L','V','1')=FLV1codec若把视频编码设为-1则将打开一个编码选择窗口(windows系统下).存储视频文件:IplImage*img=0;int nFrames=50;for(i=0;i<nFrames;i++){cvGrabFrame(capture);//抓取帧img=cvRetrieveFrame(capture);//恢复图像cvWriteFrame(writer,img);//将帧添加入视频文件}若想在抓取中查看抓取图像,可在循环中加入下列代码:cvShowImage("mainWin",img);key=cvWaitKey(20);//wait20ms 若没有20[毫秒]延迟，将无法正确显示视频序列.释放视频存储器:cvReleaseVideoWriter(&writer);。