一些常用的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_64F
     
channels: 1, 2, 3 or 4.

注意数据为交叉存取.彩色图像的数据编排为b0 g0 r0 b1 g1 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=all
int  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:

IplImage*
img=cvCreateImage(cvSize(640,480),IPL_DEPTH_8U,1);
CvScalar s;
s=cvGet2D(img,i,j); // get the (i,j) pixel value
printf(“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 value
printf(“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:

IplImage*
img=cvCreateImage(cvSize(640,480),IPL_DEPTH_32F,3);
((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 image
     
dst = byte grayscale/color image
     
flags =
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 ->
dst
     
code       
=
CV_<X>2<Y>

<X>/<Y>
= RGB, BGR, GRAY, HSV, YCrCb, XYZ, Lab, Luv, HLS
e.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1
cvLine(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(0,255,255),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 -> Vc
end{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) -> d
cvInvert(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;    
// or 30
int
frameW    
= 640; // 744 for firewire cameras
int
frameH    
= 480; // 480 for firewire cameras
writer=cvCreateVideoWriter(“out.avi”,CV_FOURCC(‘P’,’I’,’M’,’1′),

fps,cvSize(frameW,frameH),isColor);

其他有效编码:

CV_FOURCC(‘P’,’I’,’M’,’1′)      
= MPEG-1 codec
CV_FOURCC(‘M’,’J’,’P’,’G’)      
= motion-jpeg codec (does not work well)
CV_FOURCC(‘M’, ‘P’, ‘4’, ‘2’) = MPEG-4.2 codec
CV_FOURCC(‘D’, ‘I’, ‘V’, ‘3’) = MPEG-4.3 codec
CV_FOURCC(‘D’, ‘I’, ‘V’, ‘X’) = MPEG-4 codec
CV_FOURCC(‘U’, ‘2’, ‘6’, ‘3’) = H263 codec
CV_FOURCC(‘I’, ‘2’, ‘6’, ‘3’) = H263I codec
CV_FOURCC(‘F’, ‘L’, ‘V’, ‘1’) = FLV1 codec

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);             
// wait 20 ms

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);