Features Finding and Images Matching

detail::ImageFeatures

struct detail::ImageFeatures

Structure containing image keypoints and descriptors.

struct CV_EXPORTS ImageFeatures
{
    int img_idx;
    Size img_size;
    std::vector<KeyPoint> keypoints;
    Mat descriptors;
};

detail::FeaturesFinder

class detail::FeaturesFinder

Feature finders base class.

class CV_EXPORTS FeaturesFinder
{
public:
    virtual ~FeaturesFinder() {}
    void operator ()(const Mat &image, ImageFeatures &features);
    void operator ()(const Mat &image, ImageFeatures &features, const std::vector<cv::Rect> &rois);
    virtual void collectGarbage() {}

protected:
    virtual void find(const Mat &image, ImageFeatures &features) = 0;
};

detail::FeaturesFinder::operator()

Finds features in the given image.

C++: void detail::FeaturesFinder::operator()(InputArray image, ImageFeatures& features)

C++: void detail::FeaturesFinder::operator()(InputArray image, ImageFeatures& features, const std::vector<cv::Rect>& rois)

Parameters:

• image – Source image
• features – Found features
• rois – Regions of interest

See also

detail::ImageFeatures, Rect_

detail::FeaturesFinder::collectGarbage

Frees unused memory allocated before if there is any.

C++: void detail::FeaturesFinder::collectGarbage()

detail::FeaturesFinder::find

This method must implement features finding logic in order to make the wrappers detail::FeaturesFinder::operator() work.

C++: void detail::FeaturesFinder::find(InputArray image, ImageFeatures& features)

Parameters:

• image – Source image
• features – Found features

See also

detail::ImageFeatures

detail::SurfFeaturesFinder

class detail::SurfFeaturesFinder : public detail::FeaturesFinder

SURF features finder.

class CV_EXPORTS SurfFeaturesFinder : public FeaturesFinder
{
public:
    SurfFeaturesFinder(double hess_thresh = 300., int num_octaves = 3, int num_layers = 4,
                       int num_octaves_descr = /*4*/3, int num_layers_descr = /*2*/4);

private:
    /* hidden */
};

See also

detail::FeaturesFinder, SURF

detail::OrbFeaturesFinder

class detail::OrbFeaturesFinder : public detail::FeaturesFinder

ORB features finder.

class CV_EXPORTS OrbFeaturesFinder : public FeaturesFinder
{
public:
    OrbFeaturesFinder(Size _grid_size = Size(3,1), size_t n_features = 1500,
                      const ORB::CommonParams &detector_params = ORB::CommonParams(1.3f, 5));

private:
    /* hidden */
};

See also

detail::FeaturesFinder, ORB

detail::MatchesInfo

struct detail::MatchesInfo

Structure containing information about matches between two images. It’s assumed that there is a homography between those images.

struct CV_EXPORTS MatchesInfo
{
    MatchesInfo();
    MatchesInfo(const MatchesInfo &other);
    const MatchesInfo& operator =(const MatchesInfo &other);

    int src_img_idx, dst_img_idx;       // Images indices (optional)
    std::vector<DMatch> matches;
    std::vector<uchar> inliers_mask;    // Geometrically consistent matches mask
    int num_inliers;                    // Number of geometrically consistent matches
    Mat H;                              // Estimated homography
    double confidence;                  // Confidence two images are from the same panorama
};

detail::FeaturesMatcher

class detail::FeaturesMatcher

Feature matchers base class.

class CV_EXPORTS FeaturesMatcher
{
public:
    virtual ~FeaturesMatcher() {}

    void operator ()(const ImageFeatures &features1, const ImageFeatures &features2,
                     MatchesInfo& matches_info) { match(features1, features2, matches_info); }

    void operator ()(const std::vector<ImageFeatures> &features, std::vector<MatchesInfo> &pairwise_matches,
                     const Mat &mask = cv::Mat());

    bool isThreadSafe() const { return is_thread_safe_; }

    virtual void collectGarbage() {}

protected:
    FeaturesMatcher(bool is_thread_safe = false) : is_thread_safe_(is_thread_safe) {}

    virtual void match(const ImageFeatures &features1, const ImageFeatures &features2,
                       MatchesInfo& matches_info) = 0;

    bool is_thread_safe_;
};

detail::FeaturesMatcher::operator()

Performs images matching.

C++: void detail::FeaturesMatcher::operator()(const ImageFeatures& features1, const ImageFeatures& features2, MatchesInfo& matches_info)

Parameters:

• features1 – First image features
• features2 – Second image features
• matches_info – Found matches

C++: void detail::FeaturesMatcher::operator()(const std::vector<ImageFeatures>& features, std::vector<MatchesInfo>& pairwise_matches, const UMat& mask=UMat() )

Parameters:

• features – Features of the source images
• pairwise_matches – Found pairwise matches
• mask – Mask indicating which image pairs must be matched

The function is parallelized with the TBB library.

See also

detail::MatchesInfo

detail::FeaturesMatcher::isThreadSafe

C++: bool detail::FeaturesMatcher::isThreadSafe() const

Returns:True, if it’s possible to use the same matcher instance in parallel, false otherwise

detail::FeaturesMatcher::collectGarbage

Frees unused memory allocated before if there is any.

C++: void detail::FeaturesMatcher::collectGarbage()

detail::FeaturesMatcher::match

This method must implement matching logic in order to make the wrappers detail::FeaturesMatcher::operator() work.

C++: void detail::FeaturesMatcher::match(const ImageFeatures& features1, const ImageFeatures& features2, MatchesInfo& matches_info)

Parameters:

• features1 – first image features
• features2 – second image features
• matches_info – found matches

detail::BestOf2NearestMatcher

class detail::BestOf2NearestMatcher : public detail::FeaturesMatcher

Features matcher which finds two best matches for each feature and leaves the best one only if the ratio between descriptor distances is greater than the threshold match_conf.

class CV_EXPORTS BestOf2NearestMatcher : public FeaturesMatcher
{
public:
    BestOf2NearestMatcher(bool try_use_gpu = false, float match_conf = 0.65f,
                          int num_matches_thresh1 = 6, int num_matches_thresh2 = 6);

    void collectGarbage();

protected:
    void match(const ImageFeatures &features1, const ImageFeatures &features2, MatchesInfo &matches_info);

    int num_matches_thresh1_;
    int num_matches_thresh2_;
    Ptr<FeaturesMatcher> impl_;
};

See also

detail::FeaturesMatcher

detail::BestOf2NearestMatcher::BestOf2NearestMatcher

Constructs a “best of 2 nearest” matcher.

C++: detail::BestOf2NearestMatcher::BestOf2NearestMatcher(bool try_use_gpu=false, float match_conf=0.3f, int num_matches_thresh1=6, int num_matches_thresh2=6)

Parameters:

• try_use_gpu – Should try to use GPU or not
• match_conf – Match distances ration threshold
• num_matches_thresh1 – Minimum number of matches required for the 2D projective transform estimation used in the inliers classification step
• num_matches_thresh2 – Minimum number of matches required for the 2D projective transform re-estimation on inliers