The primary data structures used for image processing in OpenCV are `Mat`, `CvMat`, and `IplImage`. These structures can represent and display images, but they each have different purposes. The `Mat` type is optimized for mathematical operations and computations, making it more suitable for algorithmic tasks. On the other hand, `CvMat` and `IplImage` are designed with a focus on image handling, and they support various image-related operations like scaling, thresholding, and channel extraction.
Before OpenCV 2.0, the library was entirely implemented in C. Although there is no true object-oriented inheritance between `IplImage` and `CvMat`, their relationship resembles that of a base class and derived class. A more abstract base structure called `CvArr` is often used in the source code to handle both `CvMat` and `IplImage`.
### IplImage Structure
`IplImage` is the image header in OpenCV. It defines the structure of an image, including its size, color model, depth, and other properties. Here's a detailed breakdown:
```c
typedef struct _IplImage {
int nSize; /* Size of the IplImage structure */
int ID; /* Version (always 0) */
int nChannels; /* Number of channels (1, 2, 3, or 4) */
int alphaChannel; /* Ignored by OpenCV */
int depth; /* Pixel depth: IPL_DEPTH_8U, IPL_DEPTH_8S, etc. */
char colorModel[4]; /* Ignored by OpenCV */
char channelSeq[4]; /* Ignored by OpenCV */
int dataOrder; /* 0 = interleaved, 1 = separated */
int origin; /* 0 = top-left, 1 = bottom-left */
int align; /* Image line alignment (4 or 8) */
int width; /* Width in pixels */
int height; /* Height in pixels */
struct _IplROI *roi; /* Region of Interest */
struct _IplImage *maskROI; /* Must be NULL in OpenCV */
void *imageId; /* Same as above */
struct _IplTileInfo *tileInfo; /* Same as above */
int imageSize; /* Size of image data in bytes */
char *imageData; /* Pointer to aligned image data */
int widthStep; /* Line size in bytes */
int borderMode[4]; /* Border mode, ignored by OpenCV */
int borderConst[4]; /* Same as above */
char *imageDataOrigin; /* Pointer to unaligned image data */
} IplImage;
```
The `dataOrder` field determines whether the color channels are interleaved (e.g., BGRBGR...) or separated. The `roi` field allows you to process only a specific region of the image. Accessing pixel values can be done using indirect methods such as `cvGet2D` or direct access through the `imageData` pointer.
For example, accessing pixel values directly:
```cpp
for (int row = 0; row < img->height; row++) {
for (int col = 0; col < img->width; col++) {
unsigned char b = ((uchar*)(img->imageData + row * img->widthStep))[col * img->nChannels + 0];
unsigned char g = ((uchar*)(img->imageData + row * img->widthStep))[col * img->nChannels + 1];
unsigned char r = ((uchar*)(img->imageData + row * img->widthStep))[col * img->nChannels + 2];
}
}
```
### CvMat Structure
`CvMat` is a matrix structure used for numerical operations. It supports multi-channel data and is more abstract than traditional matrices. Its structure includes:
```c
typedef struct CvMat {
int type;
int step; /* Step in bytes */
int* refcount; /* Internal reference count */
union {
uchar* ptr;
short* s;
int* i;
float* fl;
double* db;
} data;
union {
int rows;
int height;
};
union {
int cols;
int width;
};
} CvMat;
```
Creating and accessing `CvMat` elements can be done via functions like `cvCreateMat`, `cvSet2D`, or `cvGet2D`. For multi-channel matrices, macros like `CV_MAT_ELEM` help access specific channels.
### Mat Class
Introduced in OpenCV 2.0, `Mat` is a modern replacement for `CvMat` and `IplImage`. It provides better memory management, automatic reference counting, and a more intuitive interface. `Mat` is a multidimensional dense array that can represent images, vectors, matrices, and histograms.
Key features of `Mat` include:
- Automatic memory management
- Support for multi-channel and multi-dimensional data
- Easy initialization and manipulation
Example usage:
```cpp
Mat M(7, 7, CV_32FC2, Scalar(1, 3)); // Complex matrix
Mat img(Size(320, 240), CV_8UC3); // 3-channel 8-bit image
```
Accessing elements:
```cpp
M.at(i, j); // For double type
M.at(i, j); // For single-channel 8-bit
Vec3b bgr = M.at(i, j); // For 3-channel 8-bit
```
### Conversions Between Data Types
OpenCV allows seamless conversion between `IplImage`, `CvMat`, and `Mat`:
- `IplImage` to `Mat`: `Mat mtx(iplImg);`
- `Mat` to `IplImage`: `IplImage iplImg = mtx;`
- `CvMat` to `Mat`: `Mat mtx(cvMat);`
- `Mat` to `CvMat`: `CvMat cvMat = mtx;`
These conversions allow developers to work with different data types while maintaining compatibility and efficiency.
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