cvflann::MinkowskiDistance< T > Struct Template Reference

#include "dist.h"

Public Types
typedef T	ElementType
typedef True	is_kdtree_distance
typedef True	is_vector_space_distance
typedef Accumulator< T >::Type	ResultType

Public Member Functions
	MinkowskiDistance (int order_)
template<typename U , typename V >
ResultType	accum_dist (const U &a, const V &b, int) const
template<typename Iterator1 , typename Iterator2 >
ResultType	operator() (Iterator1 a, Iterator2 b, size_t size, ResultType worst_dist=-1) const

Public Attributes
int	order

Member Typedef Documentation

template<class T>

typedef T cvflann::MinkowskiDistance< T >::ElementType

template<class T>

typedef True cvflann::MinkowskiDistance< T >::is_kdtree_distance

template<class T>

typedef True cvflann::MinkowskiDistance< T >::is_vector_space_distance

template<class T>

typedef Accumulator<T>::Type cvflann::MinkowskiDistance< T >::ResultType

Constructor & Destructor Documentation

template<class T>

cvflann::MinkowskiDistance< T >::MinkowskiDistance ( int  order_ )

inline

Member Function Documentation

template<class T>

template<typename U , typename V >

ResultType cvflann::MinkowskiDistance< T >::accum_dist ( const U &  a, const V &  b, int    ) const

inline

Partial distance, used by the kd-tree.

template<class T>

template<typename Iterator1 , typename Iterator2 >

ResultType cvflann::MinkowskiDistance< T >::operator() ( Iterator1  a, Iterator2  b, size_t  size, ResultType  worst_dist = -1  ) const

inline

Compute the Minkowsky (L_p) distance between two vectors.

This is highly optimised, with loop unrolling, as it is one of the most expensive inner loops.

The computation of squared root at the end is omitted for efficiency.

Member Data Documentation

template<class T>

int cvflann::MinkowskiDistance< T >::order

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The documentation for this struct was generated from the following file:

• flann/include/opencv2/flann/dist.h