cvflann::L1< T > Struct Template Reference

#include <dist.h>

List of all members.

Public Types
typedef True	is_kdtree_distance
typedef True	is_vector_space_distance
typedef T	ElementType
typedef Accumulator< T >::Type	ResultType
Public Member Functions
template<typename Iterator1 , typename Iterator2 >
ResultType	operator() (Iterator1 a, Iterator2 b, size_t size, ResultType worst_dist=-1) const
template<typename U , typename V >
ResultType	accum_dist (const U &a, const V &b, int) const

template<class T>
struct cvflann::L1< T >

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Member Typedef Documentation

template<class T>

typedef True cvflann::L1< T >::is_kdtree_distance

template<class T>

typedef True cvflann::L1< T >::is_vector_space_distance

template<class T>

typedef T cvflann::L1< T >::ElementType

template<class T>

typedef Accumulator<T>::Type cvflann::L1< T >::ResultType

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Member Function Documentation

template<class T>

template<typename Iterator1 , typename Iterator2 >

ResultType cvflann::L1< T >::operator()	(	Iterator1	a,
		Iterator2	b,
		size_t	size,
		ResultType	worst_dist = -1
	)		const

Compute the Manhattan (L_1) distance between two vectors.

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

template<class T>

template<typename U , typename V >

ResultType cvflann::L1< T >::accum_dist	(	const U &	a,
		const V &	b,
		int
	)		const

Partial distance, used by the kd-tree.

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

• include/opencv2/flann/dist.h