OpenCV基础知识——多维矩阵

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多维矩阵的结构分析：

例子：

#include "cv.h" 
#include "highgui.h" 
#include <stdio.h> 
#include <ctype.h> 
#include <string> 
void main()
{ 
    int size[]={2,3,4};
    CvMatND *myND=cvCreateMatND(3,size,CV_8SC1);
    printf("1 size=%d    step=%d/n",myND->dim[0]);
   printf("2 size=%d    step=%d/n",myND->dim[1]);
   printf("3 size=%d    step=%d/n",myND->dim[2]);
}

结果：

1      size=2    step=12
2      size=3    step=4
3      size=4    step=1

经过OpenCV源代码分析：

（1）在cvCreateMatND函数中先后又调用了cvCreateMatNDHeader和cvCreateData函数。

源码：

CV_IMPL CvMatND*
cvCreateMatND( int dims, const int* sizes, int type )
{
    CvMatND* arr = 0;
    CV_FUNCNAME( "cvCreateMatND" );
    
    __BEGIN__;
    CV_CALL( arr = cvCreateMatNDHeader( dims, sizes, type ));
    CV_CALL( cvCreateData( arr ));
    __END__;
    if( cvGetErrStatus() < 0 )
        cvReleaseMatND( &arr );
    return arr;
}

（2）在cvCreateMatNDHeader中，首先为CvMatND结构体分配了内存，然后接着调用了cvInitMatNDHeader函数。

源码：

CV_IMPL CvMatND*
cvCreateMatNDHeader( int dims, const int* sizes, int type )
{
    CvMatND* arr = 0;
    
    CV_FUNCNAME( "cvCreateMatNDHeader" );
    __BEGIN__;
    if( dims <= 0 || dims > CV_MAX_DIM )
        CV_ERROR( CV_StsOutOfRange,
        "non-positive or too large number of dimensions" );
    CV_CALL( arr = (CvMatND*)cvAlloc( sizeof(*arr) ));
    
    CV_CALL( cvInitMatNDHeader( arr, dims, sizes, type, 0 ));
    arr->hdr_refcount = 1;
    __END__;
    if( cvGetErrStatus() < 0 )
        cvReleaseMatND( &arr );
    return arr;
}

（3）在cvInitMatNDHeader中，其初始化了结构体CvMatND的各个成员变量。

源码：

CV_IMPL CvMatND*
cvInitMatNDHeader( CvMatND* mat, int dims, const int* sizes,
                    int type, void* data )
{
    CvMatND* result = 0;
    CV_FUNCNAME( "cvInitMatNDHeader" );
    __BEGIN__;
    type = CV_MAT_TYPE(type);
    int i;
    int64 step = CV_ELEM_SIZE(type);
    if( !mat )
        CV_ERROR( CV_StsNullPtr, "NULL matrix header pointer" );
    if( step == 0 )
        CV_ERROR( CV_StsUnsupportedFormat, "invalid array data type" );
    if( !sizes )
        CV_ERROR( CV_StsNullPtr, "NULL <sizes> pointer" );
    if( dims <= 0 || dims > CV_MAX_DIM )
        CV_ERROR( CV_StsOutOfRange,
        "non-positive or too large number of dimensions" );
    for( i = dims - 1; i >= 0; i-- )
    {
        if( sizes[i] <= 0 )
            CV_ERROR( CV_StsBadSize, "one of dimesion sizes is non-positive" );
        mat->dim[i].size = sizes[i];
        if( step > INT_MAX )
            CV_ERROR( CV_StsOutOfRange, "The array is too big" );
        mat->dim[i].step = (int)step;
        step *= sizes[i];
    }
    mat->type = CV_MATND_MAGIC_VAL | (step <= INT_MAX ? CV_MAT_CONT_FLAG : 0) | type;
    mat->dims = dims;
    mat->data.ptr = (uchar*)data;
    mat->refcount = 0;
    mat->hdr_refcount = 0;
    result = mat;
    __END__;
    if( cvGetErrStatus() < 0 && mat )
    {
        mat->type = 0;
        mat->data.ptr = 0;
    }
    return result;
}
（4）cvCrateData源码如下所示

源码：
1. CV_IMPL void
2. cvCreateData( CvArr* arr )
3. {
4. CV_FUNCNAME( "cvCreateData" );
6. __BEGIN__;
8. if( CV_IS_MAT_HDR( arr ))
9. {
10. size_t step, total_size;
11. CvMat* mat = (CvMat*)arr;
12. step = mat->step;
14. if( mat->data.ptr != 0 )
15. CV_ERROR( CV_StsError, "Data is already allocated" );
17. if( step == 0 )
18. step = CV_ELEM_SIZE(mat->type)*mat->cols;
20. total_size = step*mat->rows + sizeof(int) + CV_MALLOC_ALIGN;
21. CV_CALL( mat->refcount = (int*)cvAlloc( (size_t)total_size ));
22. mat->data.ptr = (uchar*)cvAlignPtr( mat->refcount + 1, CV_MALLOC_ALIGN );
23. *mat->refcount = 1;
24. }
25. else if( CV_IS_IMAGE_HDR(arr))
26. {
27. IplImage* img = (IplImage*)arr;
29. if( img->imageData != 0 )
30. CV_ERROR( CV_StsError, "Data is already allocated" );
32. if( !CvIPL.allocateData )
33. {
34. CV_CALL( img->imageData = img->imageDataOrigin =
35. (char*)cvAlloc( (size_t)img->imageSize ));
36. }
37. else
38. {
39. int depth = img->depth;
40. int width = img->width;
42. if( img->depth == IPL_DEPTH_32F || img->nChannels == 64 )
43. {
44. img->width *= img->depth == IPL_DEPTH_32F ? sizeof(float) : sizeof(double);
45. img->depth = IPL_DEPTH_8U;
46. }
48. CvIPL.allocateData( img, 0, 0 );
50. img->width = width;
51. img->depth = depth;
52. }
53. }
54. else if( CV_IS_MATND_HDR( arr ))
55. {
56. CvMatND* mat = (CvMatND*)arr;
57. int i;
58. size_t total_size = CV_ELEM_SIZE(mat->type);
60. if( mat->data.ptr != 0 )
61. CV_ERROR( CV_StsError, "Data is already allocated" );
63. if( CV_IS_MAT_CONT( mat->type ))
64. {
65. total_size = (size_t)mat->dim[0].size*(mat->dim[0].step != 0 ?
66. mat->dim[0].step : total_size);
67. }
68. else
69. {
70. for( i = mat->dims - 1; i >= 0; i-- )
71. {
72. size_t size = (size_t)mat->dim[i].step*mat->dim[i].size;
74. if( total_size < size )
75. total_size = size;
76. }
77. }
79. CV_CALL( mat->refcount = (int*)cvAlloc( total_size +
80. sizeof(int) + CV_MALLOC_ALIGN ));
81. mat->data.ptr = (uchar*)cvAlignPtr( mat->refcount + 1, CV_MALLOC_ALIGN );
82. *mat->refcount = 1;
83. }
84. else
85. {
86. CV_ERROR( CV_StsBadArg, "unrecognized or unsupported array type" );
87. }
89. __END__;
90. }