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This commit is contained in:
Andrey Kamaev
2012-08-07 13:29:43 +04:00
parent a3527fc4d8
commit 5100ca7508
66 changed files with 1180 additions and 1305 deletions
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98
doc/tutorials/imgproc/histograms/histogram_comparison/histogram_comparison.rst
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@@ -25,43 +25,43 @@ Theory
a. **Correlation ( CV\_COMP\_CORREL )**
.. math::
d(H_1,H_2) = \frac{\sum_I (H_1(I) - \bar{H_1}) (H_2(I) - \bar{H_2})}{\sqrt{\sum_I(H_1(I) - \bar{H_1})^2 \sum_I(H_2(I) - \bar{H_2})^2}}
d(H_1,H_2) = \frac{\sum_I (H_1(I) - \bar{H_1}) (H_2(I) - \bar{H_2})}{\sqrt{\sum_I(H_1(I) - \bar{H_1})^2 \sum_I(H_2(I) - \bar{H_2})^2}}
where
.. math::
\bar{H_k} = \frac{1}{N} \sum _J H_k(J)
\bar{H_k} = \frac{1}{N} \sum _J H_k(J)
and :math:`N` is the total number of histogram bins.
b. **Chi-Square ( CV\_COMP\_CHISQR )**
.. math::
d(H_1,H_2) = \sum _I \frac{\left(H_1(I)-H_2(I)\right)^2}{H_1(I)}
d(H_1,H_2) = \sum _I \frac{\left(H_1(I)-H_2(I)\right)^2}{H_1(I)}
c. **Intersection ( method=CV\_COMP\_INTERSECT )**
.. math::
d(H_1,H_2) = \sum _I \min (H_1(I), H_2(I))
d(H_1,H_2) = \sum _I \min (H_1(I), H_2(I))
d. **Bhattacharyya distance ( CV\_COMP\_BHATTACHARYYA )**
.. math::
d(H_1,H_2) = \sqrt{1 - \frac{1}{\sqrt{\bar{H_1} \bar{H_2} N^2}} \sum_I \sqrt{H_1(I) \cdot H_2(I)}}
d(H_1,H_2) = \sqrt{1 - \frac{1}{\sqrt{\bar{H_1} \bar{H_2} N^2}} \sum_I \sqrt{H_1(I) \cdot H_2(I)}}
Code
====
@@ -69,7 +69,7 @@ Code
.. container:: enumeratevisibleitemswithsquare
* **What does this program do?**
.. container:: enumeratevisibleitemswithsquare
* Loads a *base image* and 2 *test images* to be compared with it.
@@ -79,8 +79,8 @@ Code
* Compare the histogram of the *base image* with respect to the 2 test histograms, the histogram of the lower half base image and with the same base image histogram.
* Display the numerical matching parameters obtained.
* **Downloadable code**:
Click `here <http://code.opencv.org/svn/opencv/trunk/opencv/samples/cpp/tutorial_code/Histograms_Matching/compareHist_Demo.cpp>`_
* **Downloadable code**:
Click `here <http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/cpp/tutorial_code/Histograms_Matching/compareHist_Demo.cpp>`_
* **Code at glance:**
@@ -105,7 +105,7 @@ Code
/// Load three images with different environment settings
if( argc < 4 )
{ printf("** Error. Usage: ./compareHist_Demo <image_settings0> <image_setting1> <image_settings2>\n");
return -1;
return -1;
}
src_base = imread( argv[1], 1 );
@@ -117,7 +117,7 @@ Code
cvtColor( src_test1, hsv_test1, CV_BGR2HSV );
cvtColor( src_test2, hsv_test2, CV_BGR2HSV );
hsv_half_down = hsv_base( Range( hsv_base.rows/2, hsv_base.rows - 1 ), Range( 0, hsv_base.cols - 1 ) );
hsv_half_down = hsv_base( Range( hsv_base.rows/2, hsv_base.rows - 1 ), Range( 0, hsv_base.cols - 1 ) );
/// Using 30 bins for hue and 32 for saturation
int h_bins = 50; int s_bins = 60;
@@ -153,14 +153,14 @@ Code
/// Apply the histogram comparison methods
for( int i = 0; i < 4; i++ )
{ int compare_method = i;
{ int compare_method = i;
double base_base = compareHist( hist_base, hist_base, compare_method );
double base_half = compareHist( hist_base, hist_half_down, compare_method );
double base_test1 = compareHist( hist_base, hist_test1, compare_method );
double base_test2 = compareHist( hist_base, hist_test2, compare_method );
printf( " Method [%d] Perfect, Base-Half, Base-Test(1), Base-Test(2) : %f, %f, %f, %f \n", i, base_base, base_half , base_test1, base_test2 );
}
}
printf( "Done \n" );
@@ -171,7 +171,7 @@ Code
Explanation
===========
#. Declare variables such as the matrices to store the base image and the two other images to compare ( RGB and HSV )
#. Declare variables such as the matrices to store the base image and the two other images to compare ( RGB and HSV )
.. code-block:: cpp
@@ -186,7 +186,7 @@ Explanation
if( argc < 4 )
{ printf("** Error. Usage: ./compareHist_Demo <image_settings0> <image_setting1> <image_settings2>\n");
return -1;
return -1;
}
src_base = imread( argv[1], 1 );
@@ -205,7 +205,7 @@ Explanation
.. code-block:: cpp
hsv_half_down = hsv_base( Range( hsv_base.rows/2, hsv_base.rows - 1 ), Range( 0, hsv_base.cols - 1 ) );
hsv_half_down = hsv_base( Range( hsv_base.rows/2, hsv_base.rows - 1 ), Range( 0, hsv_base.cols - 1 ) );
#. Initialize the arguments to calculate the histograms (bins, ranges and channels H and S ).
@@ -233,7 +233,7 @@ Explanation
#. Calculate the Histograms for the base image, the 2 test images and the half-down base image:
.. code-block:: cpp
calcHist( &hsv_base, 1, channels, Mat(), hist_base, 2, histSize, ranges, true, false );
normalize( hist_base, hist_base, 0, 1, NORM_MINMAX, -1, Mat() );
@@ -252,24 +252,24 @@ Explanation
.. code-block:: cpp
for( int i = 0; i < 4; i++ )
{ int compare_method = i;
{ int compare_method = i;
double base_base = compareHist( hist_base, hist_base, compare_method );
double base_half = compareHist( hist_base, hist_half_down, compare_method );
double base_test1 = compareHist( hist_base, hist_test1, compare_method );
double base_test2 = compareHist( hist_base, hist_test2, compare_method );
printf( " Method [%d] Perfect, Base-Half, Base-Test(1), Base-Test(2) : %f, %f, %f, %f \n", i, base_base, base_half , base_test1, base_test2 );
}
printf( " Method [%d] Perfect, Base-Half, Base-Test(1), Base-Test(2) : %f, %f, %f, %f \n", i, base_base, base_half , base_test1, base_test2 );
}
Results
========
#. We use as input the following images:
============ ============ ============
============ ============ ============
|Base_0| |Test_1| |Test_2|
============ ============ ============
============ ============ ============
.. |Base_0| image:: images/Histogram_Comparison_Source_0.jpg
:align: middle
@@ -289,10 +289,10 @@ Results
=============== =============== =============== =============== ===============
*Method* Base - Base Base - Half Base - Test 1 Base - Test 2
=============== =============== =============== =============== ===============
*Correlation* 1.000000 0.930766 0.182073 0.120447
*Chi-square* 0.000000 4.940466 21.184536 49.273437
*Intersection* 24.391548 14.959809 3.889029 5.775088
*Bhattacharyya* 0.000000 0.222609 0.646576 0.801869
*Correlation* 1.000000 0.930766 0.182073 0.120447
*Chi-square* 0.000000 4.940466 21.184536 49.273437
*Intersection* 24.391548 14.959809 3.889029 5.775088
*Bhattacharyya* 0.000000 0.222609 0.646576 0.801869
=============== =============== =============== =============== ===============