openCV中的KeyPoints、DMatch、以及drawMatches函数（sift算法会用到的）

1. keypoint类

/*! The Keypoint Class The class instance stores a keypoint, i.e. a point feature found by one of many available keypoint detectors, such as Harris corner detector, cv::FAST, cv::StarDetector, cv::SURF, cv::SIFT, cv::LDetector etc.*/class  KeyPoint{public:    //! the default constructor默认构造函数    KeyPoint() : pt(0,0), size(0), angle(-1),                  response(0), octave(0), class_id(-1) {}    //! the full constructor    KeyPoint(Point2f _pt, float _size, float _angle=-1,             float _response=0, int _octave=0, int _class_id=-1)          :pt(_pt), size(_size), angle(_angle),           response(_response), octave(_octave), class_id(_class_id) {}    //! another form of the full constructor    KeyPoint(float x, float y, float _size, float _angle=-1,             float _response=0, int _octave=0, int _class_id=-1)          :pt(x, y), size(_size), angle(_angle),           response(_response), octave(_octave), class_id(_class_id) {}    size_t hash() const;    //! converts vector of keypoints to vector of points    static void convert(const vector<KeyPoint>& keypoints,                        CV_OUT vector<Point2f>& points2f,                        const vector<int>& keypointIndexes=vector<int>());    //! converts vector of points to the vector of keypoints, where each keypoint is assigned the same size and the same orientation    static void convert(const vector<Point2f>& points2f,                        CV_OUT vector<KeyPoint>& keypoints,                        float size=1, float response=1, int octave=0, int class_id=-1);    //! computes overlap for pair of keypoints;    //! overlap is a ratio between area of keypoint regions intersection and    //! area of keypoint regions union (now keypoint region is circle)    static float overlap(const KeyPoint& kp1, const KeyPoint& kp2);    Point2f pt; //!<关键点坐标coordinates of the keypoints>    float size; //!<关键点邻域直径大小diameter of the meaningful keypoint neighborhood    float angle; //!<特征点方向computed orientation of the keypoint (-1 if not applicable);                 //!< it's in [0,360) degrees and measured relative to                 //!< image coordinate system, ie in clockwise.    float response; //!< the response by which the most strong keypoints have been selected. Can be used for the further sorting or subsampling    int octave; //!<关键点所在的图像金字塔的组octave (pyramid layer) from which the keypoint has been extracted    int class_id; //!<用于聚类的ID object class (if the keypoints need to be clustered by an object they belong to)};

2.Dmatch结构

/*************************************/*             DMatch                 */*************************************//* Struct for matching: query descriptor index, train descriptor index, train image index and distance between descriptors. */struct  DMatch{//有三个构造函数    DMatch() : queryIdx(-1), trainIdx(-1), imgIdx(-1), distance(FLT_MAX) {}    DMatch( int _queryIdx, int _trainIdx, float _distance ) :            queryIdx(_queryIdx), trainIdx(_trainIdx), imgIdx(-1), distance(_distance) {}    DMatch( int _queryIdx, int _trainIdx, int _imgIdx, float _distance ) :            queryIdx(_queryIdx), trainIdx(_trainIdx), imgIdx(_imgIdx), distance(_distance) {}    CV_PROP_RW int queryIdx; //此匹配对应的查询图像的特征描述子索引 query descriptor index    CV_PROP_RW int trainIdx; //此匹配对应的训练(模板)图像的特征描述子索引 train descriptor index    CV_PROP_RW int imgIdx;   //训练图像的索引(若有多个) train image index    CV_PROP_RW float distance;//两个特征向量之间的欧氏距离，越小表明匹配度越高    // less is better    bool operator<( const DMatch &m ) const    {        return distance < m.distance;    }};

3.drawMatches函数

// Draws matches of keypints from two images on output image.void drawMatches( const Mat& img1, const vector<KeyPoint>& keypoints1,                  const Mat& img2, const vector<KeyPoint>& keypoints2,                  const vector<DMatch>& matches1to2, Mat& outIm                       const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1),                  const vector<char>& matchesMask=vector<char>(), int flags=DrawMatchesFlags::DEFAULT );void drawMatches( const Mat& img1, const vector<KeyPoint>& keypoints1,                  const Mat& img2, const vector<KeyPoint>& keypoints2,                  const vector<vector<DMatch> >& matches1to2, Mat& outImg,                  const Scalar& matchColor=Scalar::all(-1), const Scalar& singlePointColor=Scalar::all(-1),                  const vector<vector<char> >& matchesMask=vector<vector<char> >(), int flags=DrawMatchesFlags::DEFAULT );/*/*其中参数如下：* img1 – 源图像1* keypoints1 –源图像1的特征点.* img2 – 源图像2.* keypoints2 – 源图像2的特征点* matches1to2 – 源图像1的特征点匹配源图像2的特征点[matches[i]] .* outImg – 输出图像具体由flags决定.* matchColor – 匹配的颜色（特征点和连线),若matchColor==Scalar::all(-1)，颜色随机.* singlePointColor – 单个点的颜色，即未配对的特征点，若matchColor==Scalar::all(-1)，颜色随机.matchesMask – Mask决定哪些点将被画出，若为空，则画出所有匹配点.* flags – Fdefined by DrawMatchesFlags.*/