与OpenCV的第四天

第一件事：OpenCV数据结构

1. 基础图像容器 Mat 详解

• 内存：
  （1）不必再手动为其开辟空间
  （2）不必再不需要时立即释放空间
  （3）OpenCV 中使用了引用计数机制，每个 Mat 类型都有自己的信息头，但共享同一个矩阵。所以拷贝构造函数则只复制信息头和矩阵指针。
  （4）尽量不进行大图像的矩阵复制，会极大地降低程序运行速度。
  （5）当传递一个已经存在的 Mat 对象时，开辟好的矩阵会被重用。

• 组成：
  有两个部分组成：矩阵头（包含矩阵尺寸、存储方法、存储地址等信息）和指向矩阵的指针。

• 像素值的存储：
  存储像素值需要指定元素空间和数据类型。

• 颜色空间：表示存储一个指定颜色所需要的颜色元素组合。最简单的颜色空间是灰度空间，在灰度空间中只需要处理黑色原色和白色元素即可。最常用的是 RGB颜色空间，这主要是因为 RGB 颜色空间与人眼内部构成颜色的方式一致。
  颜色空间还有很多：HSV 和 HLS、YCrCb、CIE Lab*等等。

• 每个基本元素都有其自己的定义域，定义域取决于其数据类型（也就是之前所说的颜色深度），例如：char 类型（8 位）、float 类型（32 位）或 double 类型（64 位）等等。

• 创建Mat对象的几种方法：

• 直接使用 Mat() 构造函数
  原型：

    Mat(int rows, int cols, int type, const Scalar& s);

示例：

//类型格式：CV_[位数][带符号与否][类型前缀]C[通道数]
//CV_8UC3，8位3通道
Mat M(2,2, CV_8UC3, Scalar(0,0,255));

• 在 C\C++ 中通过构造函数进行初始化

int sz[3] = {2,2,2};
//参数：1.唯独，2.每个维度的尺寸，3.同上方法 4.颜色表示Scalar类（下面有介绍）
Mat L(3,sz,CV_8UC,Scalar::all(0));

• 为已存在的 IplImage 创建信息头

IplImage* img = cvLoadImage("1.jpg", 1);
Mat mtx(img) ;

• 利用 Create() 函数

cvCreateMat(int rows, int cols, int type);

• 采用 Matlab 式的初始化方式

cv::Mat::eye(int rows, int cols, int type)

• 对小矩阵采用逗号分隔式初始化函数

Mat C = (Mat_<double> (3,3) << 1, -1, 2,   -5, 5, 3,    1, 3, 1);

• 为已经存在的对象创建新的信息头

Mat RowClone = C.row(1).clone();

2. 颜色空间转换：cvtColor 函数

cvtColor 函数可以实现 RGB 颜色空间向 HSV、HSI 等颜色空间的转换。可以在 imgproc.hpp 头文件中找到，函数原型如下：

void cvtColor( InputArray src, OutputArray dst, int code, int dstCn = 0);

• 第一个参数：输入图像；
• 第二个参数：输出图像；
• 第三个参数：颜色空间转换标识符，在 imgproc.hpp 头文件的 519 行可以找到枚举定义；
• 第四个参数：目标图像通道数。

颜色空间转换标识符枚举定义

/** the color conversion code
@see @ref imgproc_color_conversions
@ingroup imgproc_misc
 */
enum ColorConversionCodes {
    COLOR_BGR2BGRA     = 0, //!< add alpha channel to RGB or BGR image
    COLOR_RGB2RGBA     = COLOR_BGR2BGRA,

    COLOR_BGRA2BGR     = 1, //!< remove alpha channel from RGB or BGR image
    COLOR_RGBA2RGB     = COLOR_BGRA2BGR,

    COLOR_BGR2RGBA     = 2, //!< convert between RGB and BGR color spaces (with or without alpha channel)
    COLOR_RGB2BGRA     = COLOR_BGR2RGBA,

    COLOR_RGBA2BGR     = 3,
    COLOR_BGRA2RGB     = COLOR_RGBA2BGR,

    COLOR_BGR2RGB      = 4,
    COLOR_RGB2BGR      = COLOR_BGR2RGB,

    COLOR_BGRA2RGBA    = 5,
    COLOR_RGBA2BGRA    = COLOR_BGRA2RGBA,

    COLOR_BGR2GRAY     = 6, //!< convert between RGB/BGR and grayscale, @ref color_convert_rgb_gray "color conversions"
    COLOR_RGB2GRAY     = 7,
    COLOR_GRAY2BGR     = 8,
    COLOR_GRAY2RGB     = COLOR_GRAY2BGR,
    COLOR_GRAY2BGRA    = 9,
    COLOR_GRAY2RGBA    = COLOR_GRAY2BGRA,
    COLOR_BGRA2GRAY    = 10,
    COLOR_RGBA2GRAY    = 11,

    COLOR_BGR2BGR565   = 12, //!< convert between RGB/BGR and BGR565 (16-bit images)
    COLOR_RGB2BGR565   = 13,
    COLOR_BGR5652BGR   = 14,
    COLOR_BGR5652RGB   = 15,
    COLOR_BGRA2BGR565  = 16,
    COLOR_RGBA2BGR565  = 17,
    COLOR_BGR5652BGRA  = 18,
    COLOR_BGR5652RGBA  = 19,

    COLOR_GRAY2BGR565  = 20, //!< convert between grayscale to BGR565 (16-bit images)
    COLOR_BGR5652GRAY  = 21,

    COLOR_BGR2BGR555   = 22,  //!< convert between RGB/BGR and BGR555 (16-bit images)
    COLOR_RGB2BGR555   = 23,
    COLOR_BGR5552BGR   = 24,
    COLOR_BGR5552RGB   = 25,
    COLOR_BGRA2BGR555  = 26,
    COLOR_RGBA2BGR555  = 27,
    COLOR_BGR5552BGRA  = 28,
    COLOR_BGR5552RGBA  = 29,

    COLOR_GRAY2BGR555  = 30, //!< convert between grayscale and BGR555 (16-bit images)
    COLOR_BGR5552GRAY  = 31,

    COLOR_BGR2XYZ      = 32, //!< convert RGB/BGR to CIE XYZ, @ref color_convert_rgb_xyz "color conversions"
    COLOR_RGB2XYZ      = 33,
    COLOR_XYZ2BGR      = 34,
    COLOR_XYZ2RGB      = 35,

    COLOR_BGR2YCrCb    = 36, //!< convert RGB/BGR to luma-chroma (aka YCC), @ref color_convert_rgb_ycrcb "color conversions"
    COLOR_RGB2YCrCb    = 37,
    COLOR_YCrCb2BGR    = 38,
    COLOR_YCrCb2RGB    = 39,

    COLOR_BGR2HSV      = 40, //!< convert RGB/BGR to HSV (hue saturation value), @ref color_convert_rgb_hsv "color conversions"
    COLOR_RGB2HSV      = 41,

    COLOR_BGR2Lab      = 44, //!< convert RGB/BGR to CIE Lab, @ref color_convert_rgb_lab "color conversions"
    COLOR_RGB2Lab      = 45,

    COLOR_BGR2Luv      = 50, //!< convert RGB/BGR to CIE Luv, @ref color_convert_rgb_luv "color conversions"
    COLOR_RGB2Luv      = 51,
    COLOR_BGR2HLS      = 52, //!< convert RGB/BGR to HLS (hue lightness saturation), @ref color_convert_rgb_hls "color conversions"
    COLOR_RGB2HLS      = 53,

    COLOR_HSV2BGR      = 54, //!< backward conversions to RGB/BGR
    COLOR_HSV2RGB      = 55,

    COLOR_Lab2BGR      = 56,
    COLOR_Lab2RGB      = 57,
    COLOR_Luv2BGR      = 58,
    COLOR_Luv2RGB      = 59,
    COLOR_HLS2BGR      = 60,
    COLOR_HLS2RGB      = 61,

    COLOR_BGR2HSV_FULL = 66, //!<
    COLOR_RGB2HSV_FULL = 67,
    COLOR_BGR2HLS_FULL = 68,
    COLOR_RGB2HLS_FULL = 69,

    COLOR_HSV2BGR_FULL = 70,
    COLOR_HSV2RGB_FULL = 71,
    COLOR_HLS2BGR_FULL = 72,
    COLOR_HLS2RGB_FULL = 73,

    COLOR_LBGR2Lab     = 74,
    COLOR_LRGB2Lab     = 75,
    COLOR_LBGR2Luv     = 76,
    COLOR_LRGB2Luv     = 77,

    COLOR_Lab2LBGR     = 78,
    COLOR_Lab2LRGB     = 79,
    COLOR_Luv2LBGR     = 80,
    COLOR_Luv2LRGB     = 81,

    COLOR_BGR2YUV      = 82, //!< convert between RGB/BGR and YUV
    COLOR_RGB2YUV      = 83,
    COLOR_YUV2BGR      = 84,
    COLOR_YUV2RGB      = 85,

    //! YUV 4:2:0 family to RGB
    COLOR_YUV2RGB_NV12  = 90,
    COLOR_YUV2BGR_NV12  = 91,
    COLOR_YUV2RGB_NV21  = 92,
    COLOR_YUV2BGR_NV21  = 93,
    COLOR_YUV420sp2RGB  = COLOR_YUV2RGB_NV21,
    COLOR_YUV420sp2BGR  = COLOR_YUV2BGR_NV21,

    COLOR_YUV2RGBA_NV12 = 94,
    COLOR_YUV2BGRA_NV12 = 95,
    COLOR_YUV2RGBA_NV21 = 96,
    COLOR_YUV2BGRA_NV21 = 97,
    COLOR_YUV420sp2RGBA = COLOR_YUV2RGBA_NV21,
    COLOR_YUV420sp2BGRA = COLOR_YUV2BGRA_NV21,

    COLOR_YUV2RGB_YV12  = 98,
    COLOR_YUV2BGR_YV12  = 99,
    COLOR_YUV2RGB_IYUV  = 100,
    COLOR_YUV2BGR_IYUV  = 101,
    COLOR_YUV2RGB_I420  = COLOR_YUV2RGB_IYUV,
    COLOR_YUV2BGR_I420  = COLOR_YUV2BGR_IYUV,
    COLOR_YUV420p2RGB   = COLOR_YUV2RGB_YV12,
    COLOR_YUV420p2BGR   = COLOR_YUV2BGR_YV12,

    COLOR_YUV2RGBA_YV12 = 102,
    COLOR_YUV2BGRA_YV12 = 103,
    COLOR_YUV2RGBA_IYUV = 104,
    COLOR_YUV2BGRA_IYUV = 105,
    COLOR_YUV2RGBA_I420 = COLOR_YUV2RGBA_IYUV,
    COLOR_YUV2BGRA_I420 = COLOR_YUV2BGRA_IYUV,
    COLOR_YUV420p2RGBA  = COLOR_YUV2RGBA_YV12,
    COLOR_YUV420p2BGRA  = COLOR_YUV2BGRA_YV12,

    COLOR_YUV2GRAY_420  = 106,
    COLOR_YUV2GRAY_NV21 = COLOR_YUV2GRAY_420,
    COLOR_YUV2GRAY_NV12 = COLOR_YUV2GRAY_420,
    COLOR_YUV2GRAY_YV12 = COLOR_YUV2GRAY_420,
    COLOR_YUV2GRAY_IYUV = COLOR_YUV2GRAY_420,
    COLOR_YUV2GRAY_I420 = COLOR_YUV2GRAY_420,
    COLOR_YUV420sp2GRAY = COLOR_YUV2GRAY_420,
    COLOR_YUV420p2GRAY  = COLOR_YUV2GRAY_420,

    //! YUV 4:2:2 family to RGB
    COLOR_YUV2RGB_UYVY = 107,
    COLOR_YUV2BGR_UYVY = 108,
    //COLOR_YUV2RGB_VYUY = 109,
    //COLOR_YUV2BGR_VYUY = 110,
    COLOR_YUV2RGB_Y422 = COLOR_YUV2RGB_UYVY,
    COLOR_YUV2BGR_Y422 = COLOR_YUV2BGR_UYVY,
    COLOR_YUV2RGB_UYNV = COLOR_YUV2RGB_UYVY,
    COLOR_YUV2BGR_UYNV = COLOR_YUV2BGR_UYVY,

    COLOR_YUV2RGBA_UYVY = 111,
    COLOR_YUV2BGRA_UYVY = 112,
    //COLOR_YUV2RGBA_VYUY = 113,
    //COLOR_YUV2BGRA_VYUY = 114,
    COLOR_YUV2RGBA_Y422 = COLOR_YUV2RGBA_UYVY,
    COLOR_YUV2BGRA_Y422 = COLOR_YUV2BGRA_UYVY,
    COLOR_YUV2RGBA_UYNV = COLOR_YUV2RGBA_UYVY,
    COLOR_YUV2BGRA_UYNV = COLOR_YUV2BGRA_UYVY,

    COLOR_YUV2RGB_YUY2 = 115,
    COLOR_YUV2BGR_YUY2 = 116,
    COLOR_YUV2RGB_YVYU = 117,
    COLOR_YUV2BGR_YVYU = 118,
    COLOR_YUV2RGB_YUYV = COLOR_YUV2RGB_YUY2,
    COLOR_YUV2BGR_YUYV = COLOR_YUV2BGR_YUY2,
    COLOR_YUV2RGB_YUNV = COLOR_YUV2RGB_YUY2,
    COLOR_YUV2BGR_YUNV = COLOR_YUV2BGR_YUY2,

    COLOR_YUV2RGBA_YUY2 = 119,
    COLOR_YUV2BGRA_YUY2 = 120,
    COLOR_YUV2RGBA_YVYU = 121,
    COLOR_YUV2BGRA_YVYU = 122,
    COLOR_YUV2RGBA_YUYV = COLOR_YUV2RGBA_YUY2,
    COLOR_YUV2BGRA_YUYV = COLOR_YUV2BGRA_YUY2,
    COLOR_YUV2RGBA_YUNV = COLOR_YUV2RGBA_YUY2,
    COLOR_YUV2BGRA_YUNV = COLOR_YUV2BGRA_YUY2,

    COLOR_YUV2GRAY_UYVY = 123,
    COLOR_YUV2GRAY_YUY2 = 124,
    //CV_YUV2GRAY_VYUY    = CV_YUV2GRAY_UYVY,
    COLOR_YUV2GRAY_Y422 = COLOR_YUV2GRAY_UYVY,
    COLOR_YUV2GRAY_UYNV = COLOR_YUV2GRAY_UYVY,
    COLOR_YUV2GRAY_YVYU = COLOR_YUV2GRAY_YUY2,
    COLOR_YUV2GRAY_YUYV = COLOR_YUV2GRAY_YUY2,
    COLOR_YUV2GRAY_YUNV = COLOR_YUV2GRAY_YUY2,

    //! alpha premultiplication
    COLOR_RGBA2mRGBA    = 125,
    COLOR_mRGBA2RGBA    = 126,

    //! RGB to YUV 4:2:0 family
    COLOR_RGB2YUV_I420  = 127,
    COLOR_BGR2YUV_I420  = 128,
    COLOR_RGB2YUV_IYUV  = COLOR_RGB2YUV_I420,
    COLOR_BGR2YUV_IYUV  = COLOR_BGR2YUV_I420,

    COLOR_RGBA2YUV_I420 = 129,
    COLOR_BGRA2YUV_I420 = 130,
    COLOR_RGBA2YUV_IYUV = COLOR_RGBA2YUV_I420,
    COLOR_BGRA2YUV_IYUV = COLOR_BGRA2YUV_I420,
    COLOR_RGB2YUV_YV12  = 131,
    COLOR_BGR2YUV_YV12  = 132,
    COLOR_RGBA2YUV_YV12 = 133,
    COLOR_BGRA2YUV_YV12 = 134,

    //! Demosaicing
    COLOR_BayerBG2BGR = 46,
    COLOR_BayerGB2BGR = 47,
    COLOR_BayerRG2BGR = 48,
    COLOR_BayerGR2BGR = 49,

    COLOR_BayerBG2RGB = COLOR_BayerRG2BGR,
    COLOR_BayerGB2RGB = COLOR_BayerGR2BGR,
    COLOR_BayerRG2RGB = COLOR_BayerBG2BGR,
    COLOR_BayerGR2RGB = COLOR_BayerGB2BGR,

    COLOR_BayerBG2GRAY = 86,
    COLOR_BayerGB2GRAY = 87,
    COLOR_BayerRG2GRAY = 88,
    COLOR_BayerGR2GRAY = 89,

    //! Demosaicing using Variable Number of Gradients
    COLOR_BayerBG2BGR_VNG = 62,
    COLOR_BayerGB2BGR_VNG = 63,
    COLOR_BayerRG2BGR_VNG = 64,
    COLOR_BayerGR2BGR_VNG = 65,

    COLOR_BayerBG2RGB_VNG = COLOR_BayerRG2BGR_VNG,
    COLOR_BayerGB2RGB_VNG = COLOR_BayerGR2BGR_VNG,
    COLOR_BayerRG2RGB_VNG = COLOR_BayerBG2BGR_VNG,
    COLOR_BayerGR2RGB_VNG = COLOR_BayerGB2BGR_VNG,

    //! Edge-Aware Demosaicing
    COLOR_BayerBG2BGR_EA  = 135,
    COLOR_BayerGB2BGR_EA  = 136,
    COLOR_BayerRG2BGR_EA  = 137,
    COLOR_BayerGR2BGR_EA  = 138,

    COLOR_BayerBG2RGB_EA  = COLOR_BayerRG2BGR_EA,
    COLOR_BayerGB2RGB_EA  = COLOR_BayerGR2BGR_EA,
    COLOR_BayerRG2RGB_EA  = COLOR_BayerBG2BGR_EA,
    COLOR_BayerGR2RGB_EA  = COLOR_BayerGB2BGR_EA,


    COLOR_COLORCVT_MAX  = 139
};

对源码中颜色空间宏的整理：

颜色空间	对应宏
RGB	RGB
RGBA	RGBA，A代表Alpha通道
BGR	BGR
BGRA	BGRA，A代表Alpha通道
5x5	BGR565、BGR555,每个数字代表每个颜色通道占几BPP （位/像素）
GRAY	GRAY
CIE XYZ	XYZ
luma-chroma (YCC)	YCrCb
HSV (hue saturation value)	HSV
CIE Lab	Lab
CIE Luv	Luv
HLS (hue lightness saturation)	HLS
YUV	YUV
Bayer	Bayer

3. 点的表示：Point 类

Point 类数据结构表示了二位坐标系下的点。
types.hpp 文件中的定义：

template<typename _Tp> class Point_
{
public:
    typedef _Tp value_type;

    // various constructors
    Point_();
    Point_(_Tp _x, _Tp _y);
    Point_(const Point_& pt);
    Point_(const Size_<_Tp>& sz);
    Point_(const Vec<_Tp, 2>& v);

    Point_& operator = (const Point_& pt);
    //! conversion to another data type
    template<typename _Tp2> operator Point_<_Tp2>() const;

    //! conversion to the old-style C structures
    operator Vec<_Tp, 2>() const;

    //! dot product
    _Tp dot(const Point_& pt) const;
    //! dot product computed in double-precision arithmetics
    double ddot(const Point_& pt) const;
    //! cross-product
    double cross(const Point_& pt) const;
    //! checks whether the point is inside the specified rectangle
    bool inside(const Rect_<_Tp>& r) const;

    _Tp x, y; //< the point coordinates
};

typedef Point_<int> Point2i;
typedef Point_<int64> Point2l;
typedef Point_<float> Point2f;
typedef Point_<double> Point2d;
typedef Point2i Point;

发现常用的 Point 是 Point_ 模板类的 int 类型 Point_<int>。
创建：

Point point;
point.x = 100;
point.y = 200;

或者

Point point = Point(100,200);

方便的运算符重载的使用：

    pt1 = pt2 + pt3;
    pt1 = pt2 - pt3;
    pt1 = pt2 * a;
    pt1 = a * pt2;
    pt1 = pt2 / a;
    pt1 += pt2;
    pt1 -= pt2;
    pt1 *= a;
    pt1 /= a;
    pt1 == pt2;
    pt1 != pt2;

4. 颜色表示：Scalar 类

在 types.hpp 中的定义：

typedef Scalar_<double> Scalar;

template<typename _Tp> class DataType< Scalar_<_Tp> >
{
public:
    typedef Scalar_<_Tp>                               value_type;
    typedef Scalar_<typename DataType<_Tp>::work_type> work_type;
    typedef _Tp                                        channel_type;

    enum { generic_type = 0,
           depth        = DataType<channel_type>::depth,
           channels     = 4,
           fmt          = DataType<channel_type>::fmt + ((channels - 1) << 8),
           type         = CV_MAKETYPE(depth, channels)
         };

    typedef Vec<channel_type, channels> vec_type;
};

发现常用的 Scalar 是 Scalar_ 模板类的 double 类型 Scalar_<double>，Scalar 包括四个颜色元素。如果用不到第四个元素可以不用写出来。

Scalar( a, b, c );

5. 尺寸表示：Size 类

在 types.hpp 头文件中的定义：

template<typename _Tp> class Size_
{
public:
    typedef _Tp value_type;

    //! various constructors
    Size_();
    Size_(_Tp _width, _Tp _height);
    Size_(const Size_& sz);
    Size_(const Point_<_Tp>& pt);

    Size_& operator = (const Size_& sz);
    //! the area (width*height)
    _Tp area() const;

    //! conversion of another data type.
    template<typename _Tp2> operator Size_<_Tp2>() const;

    _Tp width, height; // the width and the height
};

typedef Size_<int> Size2i;
typedef Size_<int64> Size2l;
typedef Size_<float> Size2f;
typedef Size_<double> Size2d;
typedef Size2i Size;

发现常用的 Size 是 Size_ 模板类的 int 类型 Size_<int>，
Size 类主要是描述宽和高的。构造方法如下：

Size(5, 5);

6. 矩形表示：Rect 类

在 types.hpp 头文件中的定义：

template<typename _Tp> class Rect_
{
public:
    typedef _Tp value_type;

    //! various constructors
    Rect_();
    Rect_(_Tp _x, _Tp _y, _Tp _width, _Tp _height);
    Rect_(const Rect_& r);
    Rect_(const Point_<_Tp>& org, const Size_<_Tp>& sz);
    Rect_(const Point_<_Tp>& pt1, const Point_<_Tp>& pt2);

    Rect_& operator = ( const Rect_& r );
    //! the top-left corner
    Point_<_Tp> tl() const;
    //! the bottom-right corner
    Point_<_Tp> br() const;

    //! size (width, height) of the rectangle
    Size_<_Tp> size() const;
    //! area (width*height) of the rectangle
    _Tp area() const;

    //! conversion to another data type
    template<typename _Tp2> operator Rect_<_Tp2>() const;

    //! checks whether the rectangle contains the point
    bool contains(const Point_<_Tp>& pt) const;

    _Tp x, y, width, height; //< the top-left corner, as well as width and height of the rectangle
};

typedef Rect_<int> Rect2i;
typedef Rect_<float> Rect2f;
typedef Rect_<double> Rect2d;
typedef Rect2i Rect;

发现常用的 Rect 是 Rect_ 模板类的 int 类型 Size_<int>，
Rect 类的成员变量有 x、y、width、height，分别为左上角点的坐标和矩形的宽和高，可以看做 point 和 size 的组合。
Rect常用运算：
两个矩形的交集、并集

Rect rect = rect1 & rect2;//交集
Rect rect = rect1 | rect2;//并集

矩阵平移、缩放

Rect rectShift = rect + point;//平移
Rect rectScale = rect + size;//缩放