Overview | Package | Class | Tree | Index | Help

OpenCV 2.4.3.1
PREV CLASS NEXT CLASS | FRAMES NO FRAMES
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD

## 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
`static int` | `BRUTEFORCE`
`static int` | `BRUTEFORCE_HAMMING`
`static int` | `BRUTEFORCE_HAMMINGLUT`
`static int` | `BRUTEFORCE_L1`
`static int` | `BRUTEFORCE_SL2`
`static int` | `FLANNBASED`
`protected long` | `nativeObj`

Constructor Summary
`protected` | `DescriptorMatcher(long addr)`

Method Summary
`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.
`protected void` | `finalize()`
`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 Trains a descriptor matcher (for example, the flann index).
`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

### nativeObj

    protected final long nativeObj

Constructor Detail

### DescriptorMatcher

    protected DescriptorMatcher(long addr)

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

### finalize

    protected void finalize()
                     throws java.lang.Throwable

  Overrides:
    `finalize` in class `java.lang.Object`
  Throws:
    `java.lang.Throwable`

### 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.
  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.
    `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.
  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.
    `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)

Overview | Package | Class | Tree | Index | Help

Official OpenCV 2.4 Documentation
PREV CLASS NEXT CLASS | FRAMES NO FRAMES
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD