org.opencv.features2d

Class DescriptorMatcher

java.lang.Object

org.opencv.features2d.DescriptorMatcher

public class DescriptorMatcher
extends java.lang.Object

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

// C++ code:

public:

virtual ~DescriptorMatcher();

virtual void add(const vector& descriptors);

const vector& 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& matches, const Mat& mask=Mat()) const;

void knnMatch(const Mat& queryDescriptors, const Mat& trainDescriptors,

vector >& matches, int k,

const Mat& mask=Mat(), bool compactResult=false) const;

void radiusMatch(const Mat& queryDescriptors, const Mat& trainDescriptors,

vector >& 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& matches,

const vector& masks=vector());

void knnMatch(const Mat& queryDescriptors, vector >& matches,

int k, const vector& masks=vector(),

bool compactResult=false);

void radiusMatch(const Mat& queryDescriptors, vector >& matches,

float maxDistance, const vector& masks=vector(),

bool compactResult=false);

virtual void read(const FileNode&);

virtual void write(FileStorage&) const;

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

static Ptr create(const string& descriptorMatcherType);

protected:

vector trainDescCollection;...

};

See Also:

org.opencv.features2d.DescriptorMatcher : public Algorithm

Field Summary

Fields

Modifier and Type	Field and Description
static int	BRUTEFORCE
static int	BRUTEFORCE_HAMMING
static int	BRUTEFORCE_HAMMINGLUT
static int	BRUTEFORCE_L1
static int	BRUTEFORCE_SL2
static int	FLANNBASED

Method Summary

Methods

Modifier and Type	Method and Description
void	add(java.util.List<Mat> descriptors) Adds descriptors to train a descriptor collection.
void	clear() Clears the train descriptor collection.
DescriptorMatcher	clone()
DescriptorMatcher	clone(boolean emptyTrainData)
static DescriptorMatcher	create(int matcherType) Creates a descriptor matcher of a given type with the default parameters (using default constructor).
boolean	empty() Returns true if there are no train descriptors in the collection.
java.util.List<Mat>	getTrainDescriptors() Returns a constant link to the train descriptor collection trainDescCollection.
boolean	isMaskSupported() Returns true if the descriptor matcher supports masking permissible matches.
void	knnMatch(Mat queryDescriptors, java.util.List<MatOfDMatch> matches, int k) Finds the k best matches for each descriptor from a query set.
void	knnMatch(Mat queryDescriptors, java.util.List<MatOfDMatch> matches, int k, java.util.List<Mat> masks, boolean compactResult) Finds the k best matches for each descriptor from a query set.
void	knnMatch(Mat queryDescriptors, Mat trainDescriptors, java.util.List<MatOfDMatch> matches, int k) Finds the k best matches for each descriptor from a query set.
void	knnMatch(Mat queryDescriptors, Mat trainDescriptors, java.util.List<MatOfDMatch> matches, int k, Mat mask, boolean compactResult) Finds the k best matches for each descriptor from a query set.
void	match(Mat queryDescriptors, Mat trainDescriptors, MatOfDMatch matches) Finds the best match for each descriptor from a query set.
void	match(Mat queryDescriptors, Mat trainDescriptors, MatOfDMatch matches, Mat mask) Finds the best match for each descriptor from a query set.
void	match(Mat queryDescriptors, MatOfDMatch matches) Finds the best match for each descriptor from a query set.
void	match(Mat queryDescriptors, MatOfDMatch matches, java.util.List<Mat> masks) Finds the best match for each descriptor from a query set.
void	radiusMatch(Mat queryDescriptors, java.util.List<MatOfDMatch> matches, float maxDistance) For each query descriptor, finds the training descriptors not farther than the specified distance.
void	radiusMatch(Mat queryDescriptors, java.util.List<MatOfDMatch> matches, float maxDistance, java.util.List<Mat> masks, boolean compactResult) For each query descriptor, finds the training descriptors not farther than the specified distance.
void	radiusMatch(Mat queryDescriptors, Mat trainDescriptors, java.util.List<MatOfDMatch> matches, float maxDistance) For each query descriptor, finds the training descriptors not farther than the specified distance.
void	radiusMatch(Mat queryDescriptors, Mat trainDescriptors, java.util.List<MatOfDMatch> matches, float maxDistance, Mat mask, boolean compactResult) For each query descriptor, finds the training descriptors not farther than the specified distance.
void	read(java.lang.String fileName)
void	train() Trains a descriptor matcher
void	write(java.lang.String fileName)

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

BRUTEFORCE

public static final int BRUTEFORCE

See Also:

Constant Field Values

BRUTEFORCE_HAMMING

public static final int BRUTEFORCE_HAMMING

See Also:

Constant Field Values

BRUTEFORCE_HAMMINGLUT

public static final int BRUTEFORCE_HAMMINGLUT

See Also:

Constant Field Values

BRUTEFORCE_L1

public static final int BRUTEFORCE_L1

See Also:

Constant Field Values

BRUTEFORCE_SL2

public static final int BRUTEFORCE_SL2

See Also:

Constant Field Values

FLANNBASED

public static final int FLANNBASED

See Also:

Constant Field Values

Method Detail

add

public void add(java.util.List<Mat> descriptors)

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

Parameters:

descriptors - Descriptors to add. Each descriptors[i] is a set of descriptors from the same train image.

See Also:

org.opencv.features2d.DescriptorMatcher.add

clear

public void clear()

Clears the train descriptor collection.

See Also:

org.opencv.features2d.DescriptorMatcher.clear

clone

public DescriptorMatcher clone()

Overrides:

clone in class java.lang.Object

clone

public DescriptorMatcher clone(boolean emptyTrainData)

create

public static DescriptorMatcher create(int matcherType)

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

Parameters:

matcherType - a matcherType

See Also:

org.opencv.features2d.DescriptorMatcher.create

empty

public boolean empty()

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

See Also:

org.opencv.features2d.DescriptorMatcher.empty

getTrainDescriptors

public java.util.List<Mat> getTrainDescriptors()

Returns a constant link to the train descriptor collection trainDescCollection.

See Also:

org.opencv.features2d.DescriptorMatcher.getTrainDescriptors

isMaskSupported

public boolean isMaskSupported()

Returns true if the descriptor matcher supports masking permissible matches.

See Also:

org.opencv.features2d.DescriptorMatcher.isMaskSupported

knnMatch

public void knnMatch(Mat queryDescriptors,
            java.util.List<MatOfDMatch> matches,
            int k)

Finds the k best matches for each descriptor from a query set.

These extended variants of "DescriptorMatcher.match" methods find several best matches for each query descriptor. The matches are returned in the distance increasing order. See "DescriptorMatcher.match" for the details about query and train descriptors.

Parameters:

queryDescriptors - Query set of descriptors.

matches - Matches. Each matches[i] is k or less matches for the same query descriptor.

k - Count of best matches found per each query descriptor or less if a query descriptor has less than k possible matches in total.

See Also:

org.opencv.features2d.DescriptorMatcher.knnMatch

knnMatch

public void knnMatch(Mat queryDescriptors,
            java.util.List<MatOfDMatch> matches,
            int k,
            java.util.List<Mat> masks,
            boolean compactResult)

Finds the k best matches for each descriptor from a query set.

These extended variants of "DescriptorMatcher.match" methods find several best matches for each query descriptor. The matches are returned in the distance increasing order. See "DescriptorMatcher.match" for the details about query and train descriptors.

Parameters:

queryDescriptors - Query set of descriptors.

matches - Matches. Each matches[i] is k or less matches for the same query descriptor.

k - Count of best matches found per each query descriptor or less if a query descriptor has less than k possible matches in total.

masks - Set of masks. Each masks[i] specifies permissible matches between the input query descriptors and stored train descriptors from the i-th image trainDescCollection[i].

compactResult - Parameter used when the mask (or masks) is not empty. If compactResult is false, the matches vector has the same size as queryDescriptors rows. If compactResult is true, the matches vector does not contain matches for fully masked-out query descriptors.

See Also:

org.opencv.features2d.DescriptorMatcher.knnMatch

knnMatch

public void knnMatch(Mat queryDescriptors,
            Mat trainDescriptors,
            java.util.List<MatOfDMatch> matches,
            int k)

Finds the k best matches for each descriptor from a query set.

These extended variants of "DescriptorMatcher.match" methods find several best matches for each query descriptor. The matches are returned in the distance increasing order. See "DescriptorMatcher.match" for the details about query and train descriptors.

Parameters:

queryDescriptors - Query set of descriptors.

trainDescriptors - Train set of descriptors. This set is not added to the train descriptors collection stored in the class object.

matches - Matches. Each matches[i] is k or less matches for the same query descriptor.

k - Count of best matches found per each query descriptor or less if a query descriptor has less than k possible matches in total.

See Also:

org.opencv.features2d.DescriptorMatcher.knnMatch

knnMatch

public void knnMatch(Mat queryDescriptors,
            Mat trainDescriptors,
            java.util.List<MatOfDMatch> matches,
            int k,
            Mat mask,
            boolean compactResult)

Finds the k best matches for each descriptor from a query set.

These extended variants of "DescriptorMatcher.match" methods find several best matches for each query descriptor. The matches are returned in the distance increasing order. See "DescriptorMatcher.match" for the details about query and train descriptors.

Parameters:

queryDescriptors - Query set of descriptors.

trainDescriptors - Train set of descriptors. This set is not added to the train descriptors collection stored in the class object.

matches - Matches. Each matches[i] is k or less matches for the same query descriptor.

k - Count of best matches found per each query descriptor or less if a query descriptor has less than k possible matches in total.

mask - Mask specifying permissible matches between an input query and train matrices of descriptors.

compactResult - Parameter used when the mask (or masks) is not empty. If compactResult is false, the matches vector has the same size as queryDescriptors rows. If compactResult is true, the matches vector does not contain matches for fully masked-out query descriptors.

See Also:

org.opencv.features2d.DescriptorMatcher.knnMatch

match

public void match(Mat queryDescriptors,
         Mat trainDescriptors,
         MatOfDMatch matches)

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(i,j) is non-zero.

Parameters:

queryDescriptors - Query set of descriptors.

trainDescriptors - Train set of descriptors. This set is not added to the train descriptors collection stored in the class object.

matches - Matches. If a query descriptor is masked out in mask, no match is added for this descriptor. So, matches size may be smaller than the query descriptors count.

See Also:

org.opencv.features2d.DescriptorMatcher.match

match

public void match(Mat queryDescriptors,
         Mat trainDescriptors,
         MatOfDMatch matches,
         Mat mask)

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(i,j) is non-zero.

Parameters:

queryDescriptors - Query set of descriptors.

trainDescriptors - Train set of descriptors. This set is not added to the train descriptors collection stored in the class object.

matches - Matches. If a query descriptor is masked out in mask, no match is added for this descriptor. So, matches size may be smaller than the query descriptors count.

mask - Mask specifying permissible matches between an input query and train matrices of descriptors.

See Also:

org.opencv.features2d.DescriptorMatcher.match

match

public void match(Mat queryDescriptors,
         MatOfDMatch matches)

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(i,j) is non-zero.

Parameters:

queryDescriptors - Query set of descriptors.

matches - Matches. If a query descriptor is masked out in mask, no match is added for this descriptor. So, matches size may be smaller than the query descriptors count.

See Also:

org.opencv.features2d.DescriptorMatcher.match

match

public void match(Mat queryDescriptors,
         MatOfDMatch matches,
         java.util.List<Mat> masks)

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(i,j) is non-zero.

Parameters:

queryDescriptors - Query set of descriptors.

matches - Matches. If a query descriptor is masked out in mask, no match is added for this descriptor. So, matches size may be smaller than the query descriptors count.

masks - Set of masks. Each masks[i] specifies permissible matches between the input query descriptors and stored train descriptors from the i-th image trainDescCollection[i].

See Also:

org.opencv.features2d.DescriptorMatcher.match

radiusMatch

public void radiusMatch(Mat queryDescriptors,
               java.util.List<MatOfDMatch> matches,
               float maxDistance)

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.

Parameters:

queryDescriptors - Query set of descriptors.

matches - Found matches.

maxDistance - Threshold for the distance between matched descriptors. Distance means here metric distance (e.g. Hamming distance), not the distance between coordinates (which is measured in Pixels)!

See Also:

org.opencv.features2d.DescriptorMatcher.radiusMatch

radiusMatch

public void radiusMatch(Mat queryDescriptors,
               java.util.List<MatOfDMatch> matches,
               float maxDistance,
               java.util.List<Mat> masks,
               boolean compactResult)

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.

Parameters:

queryDescriptors - Query set of descriptors.

matches - Found matches.

maxDistance - Threshold for the distance between matched descriptors. Distance means here metric distance (e.g. Hamming distance), not the distance between coordinates (which is measured in Pixels)!

masks - Set of masks. Each masks[i] specifies permissible matches between the input query descriptors and stored train descriptors from the i-th image trainDescCollection[i].

compactResult - Parameter used when the mask (or masks) is not empty. If compactResult is false, the matches vector has the same size as queryDescriptors rows. If compactResult is true, the matches vector does not contain matches for fully masked-out query descriptors.

See Also:

org.opencv.features2d.DescriptorMatcher.radiusMatch

radiusMatch

public void radiusMatch(Mat queryDescriptors,
               Mat trainDescriptors,
               java.util.List<MatOfDMatch> matches,
               float maxDistance)

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.

Parameters:

queryDescriptors - Query set of descriptors.

trainDescriptors - Train set of descriptors. This set is not added to the train descriptors collection stored in the class object.

matches - Found matches.

maxDistance - Threshold for the distance between matched descriptors. Distance means here metric distance (e.g. Hamming distance), not the distance between coordinates (which is measured in Pixels)!

See Also:

org.opencv.features2d.DescriptorMatcher.radiusMatch

radiusMatch

public void radiusMatch(Mat queryDescriptors,
               Mat trainDescriptors,
               java.util.List<MatOfDMatch> matches,
               float maxDistance,
               Mat mask,
               boolean compactResult)

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.

Parameters:

queryDescriptors - Query set of descriptors.

trainDescriptors - Train set of descriptors. This set is not added to the train descriptors collection stored in the class object.

matches - Found matches.

maxDistance - Threshold for the distance between matched descriptors. Distance means here metric distance (e.g. Hamming distance), not the distance between coordinates (which is measured in Pixels)!

mask - Mask specifying permissible matches between an input query and train matrices of descriptors.

compactResult - Parameter used when the mask (or masks) is not empty. If compactResult is false, the matches vector has the same size as queryDescriptors rows. If compactResult is true, the matches vector does not contain matches for fully masked-out query descriptors.

See Also:

org.opencv.features2d.DescriptorMatcher.radiusMatch

read

public void read(java.lang.String fileName)

train

public void 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).

See Also:

org.opencv.features2d.DescriptorMatcher.train

write

public void write(java.lang.String fileName)