OpenCV(三) 之 基本数据结构 CvMat和 IplImage

OpenCV(三) 之 基本数据结构 CvMat和 IplImage

CvMat

IplImage

OpenCv中基本的数据类型

类型	参数	表示
CvPoint	int x,y	像素点
CvPoint2D32f	float x,y	平面点
CvPoint3D32f	float x,y,z	空间点
CvSize	int width,height	图像大小
CvSize2D32f	float　x, y	区域大小
CvSize3D32f	float x,y,z	立方体大小
CvRect	int x,y,width,height	矩形区域
CvScalar	double val[4]	RGBA 值

类型的构造函数仅是类型名首字母小写，比如cvPoint(int x,int y)，除了CvScalar

CvScalar类型是可以用来存放4个double类型的数组，最多四个不一定要四个

1. typedef struct CvScalar 

   ---

2. { 

   ---

3. double val[4]; 

   ---

4. }; 

   ---

其赋值函数有四种

1. 1. CvScalar cvScalar(double v0,double v1,double v2, double v3); 

   ---

2. 2. CvScalar cvRealScalar(double v0); 

   ---

3. //第一个数值赋值，剩余三个为0 

   ---

4. 3. CvScalar cvScalarAll(double v); 

   ---

5. //所有的四个值都相同 

   ---

6. 4. CV_RGB 

   ---

7. #define CV_RGB(r,g,b) cvScalar(b,r,g,0); 

   ---

CvMat类型

1. typedef struct CvMat { 

   ---

2. int type; 

   ---

3. int step; 

   ---

4. int* refcount; // for internal use only 

   ---

5. union { 

   ---

6. uchar* ptr; 

   ---

7. short* s; 

   ---

8. int* i; 

   ---

9. float* fl; 

   ---

10. double* db; 

    ---

11. } data; 

    ---

12. union { 

    ---

13. int rows; 

    ---

14. int height; 

    ---

15. }; 

    ---

16. union { 

    ---

17. int cols; 

    ---

18. int width; 

    ---

19. }; 

    ---

20. } CvMat; 

    ---

其构造函数

1. CvMat* cvCreateMat(int rows,int cols,int type); 

   ---

2. CvMat* cvCreateMatHeader(int rows,int cols,int type); 

   ---

3. CvMat* cvInitMatHeader(CvMat *mat,int rows,int cols,int type, void* data=NULL, int step = CV_AUTOSTEP) 

   ---

4. CvMat* cvCloneMat(CvMat*) 

   ---

5.  

   ---

6. //内存释放 

   ---

7. void cvReleaseMat(CvMat** mat) 

   ---

使用数组创建CvMat

1. float vals[4]=[1,2,3,4]; 

   ---

2. CvMat* mat; 

   ---

3. cvInitMatHeader(mat,2,2,CV_32FC1,vals); 

   ---

CvMat属性值的获取

1. cvGetElemType(const CvArr* arr);//返回数据类型 

   ---

2. cvGetDims(const CvArr* arr,int* sizes=NULL);//返回CvMat的维数，相当于张量的阶数， int* 可以用来存储每一维对应的长度 

   ---

3. cvGetDimSize(const CvArr* arr,int index);//返回第index维度上的长度 

   ---

CvMat数据值的读取

1. float sum( const CvMat* mat )  

   ---

2. { 

   ---

3. float s = 0.0f; 

   ---

4. for(int row=0; row<mat->rows; row++ )  

   ---

5. { 

   ---

6. const float* ptr = (const float*)(mat->data.ptr + row * mat->step); 

   ---

7. for( col=0; col<mat->cols; col++ ) 

   ---

8. { 

   ---

9. s += *ptr++; 

   ---

10. } 

    ---

11. } 

    ---

12. return( s ); 

    ---

13. } 

    ---

这里要注意的是

1. 要强制指定数据类型，因为CvMat定义中数据类型是union。

2. 使用step参数是每一行所占的字节数，并不等于cols*sizeof(bytes),因为含有优化的地址对齐问题。

CvMat矩阵数据存储顺序是先行再列，3D数据存储顺序是每个位置的channels，然后按行、列排列。

下图时一组空间点存到不同的CvMat的存储结果

1477837579893.jpg

IplImage

1. typedef struct _IplImage{ 

   ---

2. int nSize; 

   ---

3. int ID; 

   ---

4. int nChannels; //**type 

   ---

5. int alphaChannel; 

   ---

6. int depth; //**type 

   ---

7. int dataOrder; //数组存储结构，是按照像素存IPL_DATA_ORDER_PIXEL,还是先按照通道存IPL_DATA_ORDER_PLANE 

   ---

8. int origin; //图像坐标原点位于左上角 IPL_ORIGIN_TL，还是左下角IPL_ORIGIN_BL 

   ---

9. int align; 

   ---

10. int width; //**columns 

    ---

11. int height; //**rows 

    ---

12. char colorModel[4]; 

    ---

13. char channelSeq[4]; 

    ---

14. struct _IplROI* roi; //region of interest 

    ---

15. struct _IplImage* maskROI; 

    ---

16. void* imageId; 

    ---

17. struct _IplTileInfo* tileInfo; 

    ---

18. int imageSize; 

    ---

19. char* imageData; //** data 

    ---

20. int widthStep; //** step 

    ---

21. int BorderMode[4]; 

    ---

22. int BorderConst[4]; 

    ---

23. char* imageDataOrigin; 

    ---

24. } 

    ---

其中注释**部分对应着CvMat的成员变量，CvMat的type成员被拆分成了两个属性：depth, nChannels表示像素值深度和图像的通道数
depth的取值有

1. IPL_DEPTH_8U; IPL_DEPTH_8S; IPL_DEPTH_16S; IPL_DEPTH_32S; IPL_DEPTH_32F; IPL_DEPTH_64F; 

   ---

看字面就知道什么意思了。

IplROI包含的属性:

1. int xOffset, yOffset; //x,y 方向的偏置 

   ---

2. int height, width; //感兴趣区域的大小 

   ---

3. int COI; //Channel of Interest,感兴趣的通道 

   ---

一旦ROI设置了，那么对图像的操作将尽在ROI内操作。

IplImage数据的访问示例

对于HSV图像，希望将S，V通道值设置为255：

1. void saturate_sv(IplImage* img) 

   ---

2. { 

   ---

3. for(int y=0;y<img->height;y++) 

   ---

4. { 

   ---

5. uchar* ptr=(uchar*)(img->imageData+y*img->widthStep); 

   ---

6. for(int x=0;x<img->width;i++) 

   ---

7. { 

   ---

8. ptr[3*x+1]=255; 

   ---

9. ptr[3*x+2]=255; 

   ---

10. } 

    ---

11. } 

    ---

12. } 

    ---

这里奇怪为什么默认img->dataOrder=IPL_DATA_ORDER_PIXEL。这是因为

We say that dataOrder may be either IPL_DATA_ORDER_PIXEL of IPL_DATA_ORDER_PLANE, but in fact only IPL_DATA_ORDER_PIXEL is supported by OpenCV. Both values are generally supported by IPL/IPP, but OpenCV always uses interleaved images.

Note: 比较CvMat和IplImage数据区的操作，发现IplImage->imageData并没有进行类型转换，全部都是byte字节，而CvMat则需要转换成所存储数据的类型，在指针运算时需要特别注意，尤其是IplImage和CvMat进行计算时。

ROI的使用:

1. void cvSetImageROI(IplImage* image, CvRect rect); //设置rect区域为感兴趣区域 

   ---

2. void cvResetImageROI(IplImage* image); //取消图像的感兴趣区域 

   ---

1. #include "highgui.h" 

   ---

2. #include "cv.h" 

   ---

3. int main(int argc, char** argv) 

   ---

4. { 

   ---

5. // 图像路径、ROI的x,y偏移量, 长和宽、像素值增加量 

   ---

6. IplImage* src; 

   ---

7. if (argc == 7 && ((src = cvLoadImage(argv[1])) != 0)) 

   ---

8. { 

   ---

9. int xOffset = atoi(argv[2]); //x偏移 

   ---

10. int yOffset = atoi(argv[3]); //y偏移 

    ---

11. int width = atoi(argv[4]); //ROI宽 

    ---

12. int height = atoi(argv[5]); //ROI高 

    ---

13. int add = atoi(argv[6]); //每个像素值增加量 

    ---

14.  

    ---

15. cvSetImageROI(src, cvRect(xOffset, yOffset, width, height)); 

    ---

16. cvAddS(src, cvScalarAll(add), src); 

    ---

17. cvResetImageROI(src); 

    ---

18. cvNamedWindow("src"); 

    ---

19. cvShowImage("src", src); 

    ---

20. cvWaitKey(0); 

    ---

21. cvReleaseImage(&src); 

    ---

22. cvDestroyWindow("src"); 

    ---

23.  

    ---

24. } 

    ---

25.  

    ---

26. } 

    ---

1478005187960.jpg

上述过程还存在另一种直接地址操作的方法

1. #include "highgui.h" 

   ---

2. #include "cv.h" 

   ---

3. int main(int argc, char** argv) 

   ---

4. { 

   ---

5. // 图像路径、ROI的x,y偏移量, 长和宽、像素值增加量 

   ---

6. IplImage* src; 

   ---

7. if (argc == 7 && ((src = cvLoadImage(argv[1])) != 0)) 

   ---

8. { 

   ---

9. int xOffset = atoi(argv[2]); //x偏移 

   ---

10. int yOffset = atoi(argv[3]); //y偏移 

    ---

11. int width = atoi(argv[4]); //ROI宽 

    ---

12. int height = atoi(argv[5]); //ROI高 

    ---

13. int add = atoi(argv[6]); //每个像素值增加量 

    ---

14.  

    ---

15. IplImage * sub_img = cvCreateImageHeader(cvSize(width, height), src->depth, src->nChannels); 

    ---

16. sub_img->widthStep = src->widthStep; 

    ---

17. sub_img->imageData = src->imageData + yOffset*src->widthStep + xOffset*src->nChannels; 

    ---

18.  

    ---

19. cvAddS(sub_img, cvScalarAll(add), sub_img); 

    ---

20. cvReleaseImageHeader(&sub_img); 

    ---

21.  

    ---

22. cvResetImageROI(src); 

    ---

23. cvNamedWindow("src"); 

    ---

24. cvShowImage("src", src); 

    ---

25. cvWaitKey(0); 

    ---

26. cvReleaseImage(&src); 

    ---

27. cvDestroyWindow("src"); 

    ---

28.  

    ---

29. } 

    ---

30.  

    ---

31. } 

    ---

这里很容易理解，就是将ROI截取出来作为一个新的图像，需要注意的时sub_img并没有新分配地址，数据区指向的仍然是src的数据区，此时图像sub_img的数据区并不是连续的，所以将src->widthStep赋值给sub_img-》widthStep保证读取正确的地址数据。