common_interfaces_of_descriptor_matchers.rst



Common Interfaces of Descriptor Matchers
Matchers of keypoint descriptors in OpenCV have wrappers with a common interface that enables you to easily switch
between different algorithms solving the same problem. This section is devoted to matching descriptors
that are represented as vectors in a multidimensional space. All objects that implement vector
descriptor matchers inherit the
:ocv:class:`DescriptorMatcher` interface.

Note

An example explaining keypoint matching can be found at opencv_source_code/samples/cpp/descriptor_extractor_matcher.cpp
An example on descriptor matching evaluation can be found at opencv_source_code/samples/cpp/detector_descriptor_matcher_evaluation.cpp
An example on one to many image matching can be found at opencv_source_code/samples/cpp/matching_to_many_images.cpp


DescriptorMatcher
Abstract base class for matching keypoint descriptors. It has two groups
of match methods: for matching descriptors of an image with another image or
with an image set.
class DescriptorMatcher
{
public:
    virtual ~DescriptorMatcher();

    virtual void add( const vector<Mat>& descriptors );

    const vector<Mat>& getTrainDescriptors() const;
    virtual void clear();
    bool empty() const;
    virtual bool isMaskSupported() const = 0;

    virtual void train();

    /*
     * Group of methods to match descriptors from an image pair.
     */
    void match( const Mat& queryDescriptors, const Mat& trainDescriptors,
                vector<DMatch>& matches, const Mat& mask=Mat() ) const;
    void knnMatch( const Mat& queryDescriptors, const Mat& trainDescriptors,
                   vector<vector<DMatch> >& matches, int k,
                   const Mat& mask=Mat(), bool compactResult=false ) const;
    void radiusMatch( const Mat& queryDescriptors, const Mat& trainDescriptors,
                      vector<vector<DMatch> >& matches, float maxDistance,
                      const Mat& mask=Mat(), bool compactResult=false ) const;
    /*
     * Group of methods to match descriptors from one image to an image set.
     */
    void match( const Mat& queryDescriptors, vector<DMatch>& matches,
                const vector<Mat>& masks=vector<Mat>() );
    void knnMatch( const Mat& queryDescriptors, vector<vector<DMatch> >& matches,
                   int k, const vector<Mat>& masks=vector<Mat>(),
                   bool compactResult=false );
    void radiusMatch( const Mat& queryDescriptors, vector<vector<DMatch> >& matches,
                      float maxDistance, const vector<Mat>& masks=vector<Mat>(),
                      bool compactResult=false );

    virtual void read( const FileNode& );
    virtual void write( FileStorage& ) const;

    virtual Ptr<DescriptorMatcher> clone( bool emptyTrainData=false ) const = 0;

    static Ptr<DescriptorMatcher> create( const String& descriptorMatcherType );

protected:
    vector<Mat> trainDescCollection;
    ...
};


DescriptorMatcher::add
Adds descriptors to train a descriptor collection. If the collection trainDescCollectionis is not empty, the new descriptors are added to existing train descriptors.

DescriptorMatcher::getTrainDescriptors
Returns a constant link to the train descriptor collection trainDescCollection .

DescriptorMatcher::clear
Clears the train descriptor collection.

DescriptorMatcher::empty
Returns true if there are no train descriptors in the collection.

DescriptorMatcher::isMaskSupported
Returns true if the descriptor matcher supports masking permissible matches.

DescriptorMatcher::train
Trains a descriptor matcher
Trains a descriptor matcher (for example, the flann index). In all methods to match, the method train() is run every time before matching. Some descriptor matchers (for example, BruteForceMatcher) have an empty implementation of this method. Other matchers really train their inner structures (for example, FlannBasedMatcher trains flann::Index ).

DescriptorMatcher::match
Finds the best match for each descriptor from a query set.
In the first variant of this method, the train descriptors are passed as an input argument. In the second variant of the method, train descriptors collection that was set by DescriptorMatcher::add is used. Optional mask (or masks) can be passed to specify which query and training descriptors can be matched. Namely, queryDescriptors[i] can be matched with trainDescriptors[j] only if mask.at<uchar>(i,j) is non-zero.

DescriptorMatcher::knnMatch
Finds the k best matches for each descriptor from a query set.
These extended variants of :ocv:func:`DescriptorMatcher::match` methods find several best matches for each query descriptor. The matches are returned in the distance increasing order. See :ocv:func:`DescriptorMatcher::match` for the details about query and train descriptors.

DescriptorMatcher::radiusMatch
For each query descriptor, finds the training descriptors not farther than the specified distance.
For each query descriptor, the methods find such training descriptors that the distance between the query descriptor and the training descriptor is equal or smaller than maxDistance. Found matches are returned in the distance increasing order.

DescriptorMatcher::clone
Clones the matcher.

DescriptorMatcher::create
Creates a descriptor matcher of a given type with the default parameters (using default constructor).

BFMatcher
Brute-force descriptor matcher. For each descriptor in the first set, this matcher finds the closest descriptor in the second set by trying each one. This descriptor matcher supports masking permissible matches of descriptor sets.

BFMatcher::BFMatcher
Brute-force matcher constructor.

FlannBasedMatcher
Flann-based descriptor matcher. This matcher trains :ocv:class:`flann::Index_` on a train descriptor collection and calls its nearest search methods to find the best matches. So, this matcher may be faster when matching a large train collection than the brute force matcher. FlannBasedMatcher does not support masking permissible matches of descriptor sets because flann::Index does not support this.
class FlannBasedMatcher : public DescriptorMatcher
{
public:
    FlannBasedMatcher(
      const Ptr<flann::IndexParams>& indexParams=new flann::KDTreeIndexParams(),
      const Ptr<flann::SearchParams>& searchParams=new flann::SearchParams() );

    virtual void add( const vector<Mat>& descriptors );
    virtual void clear();

    virtual void train();
    virtual bool isMaskSupported() const;

    virtual Ptr<DescriptorMatcher> clone( bool emptyTrainData=false ) const;
protected:
    ...
};