Code for the
Earth Movers Distance (EMD) 
[View
this page in Portuguese courtesy of Adelina Domingos and Artur Weber]
[View
this page in Romanian courtesy of azoft]
[View this page in German courtesy of Kate Bondareva]
[View this page in Russian courtesy of Oleg Meister]
[View this page in Danish courtesy of Dream Team]
[View this page in Italian courtesy of Gracy Laura]
[View this page in Irish courtesy of TravelTicker.com]
[View this page in Indonesian courtesy of ChameleonJohn.com]
[View this page in Spanish courtesy of Coupon Goo.] 
Introduction 
This is an implementation of the Earth Movers Distance, as described in [1].
The EMD computes the distance between two distributions,
which are represented by signatures. The signatures are sets of weighted features that
capture the distributions. The features can be of any type and in any number of
dimensions, and are defined by the user. The EMD is defined as the minimum amount of
work needed to change one signature into the other. The notion of "work" is
based on the userdefined ground distance which is the distance between two features. The
size of the two signatures can be different. Also, the sum of weights of one signature can
be different than the sum of weights of the other (partial match). Because of this, the
EMD is normalized by the smaller sum.
The code is implemented in C, and is based on the solution for the Transportation
problem as described in [2]
Please let me know of any bugs you find, or
any questions, comments, suggestions, and criticisms you have. If you find this code
useful for your work, I would like very much to hear from you. Once you do, I'll inform
you of any improvements, etc. Also, an acknowledgment in any publication describing work
that uses this code would be greatly appreciated.

Usage 
To use the code, perform the following steps:
 download the files
emd.h and emd.c
(check the log of changes for latest changes).
 In
emd.h , modify the line typedef int feature_t;
to reflect your feature data type. Structures may be used too, for example
typedef struct {
int X,Y,Z;
} feature_t;
 To compute an EMD, call:
float emd(signature_t *Signature1, signature_t *Signature2,
float (*func)(feature_t *, feature_t *),
flow_t *Flow, int *FlowSize);
where
Signature1, Signature2 :
 Pointers to the two signatures that their distance we want to compute.
Dist :
 Pointer to the ground distance function. i.e. the function that computes the distance
between two features.
Flow :
 (Optional) Pointer to a vector of flow_t (defined in emd.h) where the resulting flow
will be stored. Flow must have n1+n21 elements, where n1 and n2 are the sizes of the two
signatures respectively. If
NULL , the flow is not returned.
FlowSize :
 (Optional) In case
Flow is not NULL , FlowSize
should point to a integer where the number of flow elements (always less or equal to
n1+n21) will be written.
 Compile
emd.c and link it to your code.
The signature data type signature_t is defined in emd.h as:
typedef struct
{
int n; /* Number of features in the distribution */
feature_t *Features; /* Pointer to the features vector */
float *Weights; /* Pointer to the weights of the features */
} signature_t;
The feature data type feature_t is defined in emd.h and
should be modified by the user to reflect his feature type.
In special cases, the user might want to change some of the values in the definitions
in emd.h :
#define MAX_SIG_SIZE 100
 The maximum allowed number of features in a signature
#define MAX_ITERATIONS 100
 Maximum number of iterations. For ordinary problems, 100 should be more than enough.
#define INFINITY 1e20
INFINITY should be much larger than any other
value in the problem
#define EPSILON 1e6
EPSILON determines the accuracy of the
solution.


Examples 
example1.c
In this example the features are in threedimensional space, and the ground distance is
the Euclidean distance.
To try this example, you need to modify feature_t in emd.h to be
typedef struct { int X,Y,Z; } feature_t;
example2.c
Here, instead of providing a function to compute the ground distances, they are given in a
predefined matrix. This is done by defining feature_t as int
(the default), and setting the features in each signature to have consecutive numbers. The
ground distance function uses these numbers as indexes to the predefined cost matrix.
The resulting flow is returned from the emd function by passing as the last
parameters a vector of flow_t , and a pointer to int where the
actual number of flow elements will be written.
Also, in this example the total weights of the two signatures are different. The first
signature has a total weight of 1 while the second signature has a total weight of 0.9.

Log of changes 
Date 
Decription 
05/10/98 
Changed from absolute error check to relative error check + Fixed a bug that caused
the "Unexpected error in findBasicVariables" error message (thanks Mark Ruzon) 
03/04/98 
Fixed a bug that sometime caused a crash when the second signature had only one
feature (thanks Mark Ruzon) 
03/31/98 
Fixed a bug in the case where *both* signatures have only one feature (thanks Rajesh
Batra) 

References 
[1] Y. Rubner, C. Tomasi,
and L. J. Guibas.
A Metric
for Distributions with Applications to Image Databases. Proceedings of the 1998
IEEE International Conference on Computer Vision, Bombay, India, January 1998, pp.
5966.
[2] F. S. Hillier and G. J. Lieberman. Introduction to Mathematical
Programming McGrawHill, 1990. 