@Namespace(value="cv") @NoOffset public static class opencv_features2d.BFMatcher extends opencv_features2d.DescriptorMatcher
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.
Pointer.CustomDeallocator, Pointer.Deallocator, Pointer.NativeDeallocator| Constructor and Description |
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opencv_features2d.BFMatcher() |
opencv_features2d.BFMatcher(int normType,
boolean crossCheck)
\brief Brute-force matcher constructor.
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opencv_features2d.BFMatcher(long size)
Native array allocator.
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opencv_features2d.BFMatcher(Pointer p)
Pointer cast constructor.
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| Modifier and Type | Method and Description |
|---|---|
opencv_features2d.DescriptorMatcher |
clone() |
opencv_features2d.DescriptorMatcher |
clone(boolean emptyTrainData)
\brief Clones the matcher.
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boolean |
isMaskSupported()
\brief Returns true if the descriptor matcher supports masking permissible matches.
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opencv_features2d.BFMatcher |
position(long position) |
add, clear, create, create, empty, getTrainDescriptors, knnMatch, knnMatch, knnMatch, knnMatch, match, match, match, match, radiusMatch, radiusMatch, radiusMatch, radiusMatch, read, train, writegetDefaultName, save, saveaddress, asBuffer, asByteBuffer, capacity, capacity, close, deallocate, deallocate, deallocateReferences, deallocator, deallocator, equals, fill, hashCode, isNull, limit, limit, maxBytes, memchr, memcmp, memcpy, memmove, memset, offsetof, position, put, setNull, sizeof, toString, totalBytes, withDeallocator, zeropublic opencv_features2d.BFMatcher(Pointer p)
Pointer.Pointer(Pointer).public opencv_features2d.BFMatcher(long size)
Pointer.position(long).public opencv_features2d.BFMatcher(int normType,
@Cast(value="bool")
boolean crossCheck)
normType - One of NORM_L1, NORM_L2, NORM_HAMMING, NORM_HAMMING2. L1 and L2 norms are
preferable choices for SIFT and SURF descriptors, NORM_HAMMING should be used with ORB, BRISK and
BRIEF, NORM_HAMMING2 should be used with ORB when WTA_K==3 or 4 (see ORB::ORB constructor
description).crossCheck - If it is false, this is will be default BFMatcher behaviour when it finds the k
nearest neighbors for each query descriptor. If crossCheck==true, then the knnMatch() method with
k=1 will only return pairs (i,j) such that for i-th query descriptor the j-th descriptor in the
matcher's collection is the nearest and vice versa, i.e. the BFMatcher will only return consistent
pairs. Such technique usually produces best results with minimal number of outliers when there are
enough matches. This is alternative to the ratio test, used by D. Lowe in SIFT paper.public opencv_features2d.BFMatcher()
public opencv_features2d.BFMatcher position(long position)
position in class opencv_core.Algorithm@Cast(value="bool") public boolean isMaskSupported()
opencv_features2d.DescriptorMatcherisMaskSupported in class opencv_features2d.DescriptorMatcher@opencv_core.Ptr public opencv_features2d.DescriptorMatcher clone(@Cast(value="bool") boolean emptyTrainData)
opencv_features2d.DescriptorMatcherclone in class opencv_features2d.DescriptorMatcheremptyTrainData - If emptyTrainData is false, the method creates a deep copy of the object,
that is, copies both parameters and train data. If emptyTrainData is true, the method creates an
object copy with the current parameters but with empty train data.@opencv_core.Ptr public opencv_features2d.DescriptorMatcher clone()
clone in class opencv_features2d.DescriptorMatcherCopyright © 2016. All rights reserved.