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257 lines
9.3 KiB
Markdown
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Eroding and Dilating {#tutorial_erosion_dilatation}
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====================
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Goal
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----
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In this tutorial you will learn how to:
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- Apply two very common morphology operators: Dilation and Erosion. For this purpose, you will use
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the following OpenCV functions:
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- @ref cv::erode
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- @ref cv::dilate
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Cool Theory
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-----------
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@note The explanation below belongs to the book **Learning OpenCV** by Bradski and Kaehler.
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Morphological Operations --------------------------
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- In short: A set of operations that process images based on shapes. Morphological operations
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apply a *structuring element* to an input image and generate an output image.
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- The most basic morphological operations are two: Erosion and Dilation. They have a wide array of
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uses, i.e. :
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- Removing noise
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- Isolation of individual elements and joining disparate elements in an image.
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- Finding of intensity bumps or holes in an image
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- We will explain dilation and erosion briefly, using the following image as an example:
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![image](images/Morphology_1_Tutorial_Theory_Original_Image.png)
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### Dilation
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- This operations consists of convoluting an image \f$A\f$ with some kernel (\f$B\f$), which can have any
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shape or size, usually a square or circle.
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- The kernel \f$B\f$ has a defined *anchor point*, usually being the center of the kernel.
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- As the kernel \f$B\f$ is scanned over the image, we compute the maximal pixel value overlapped by
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\f$B\f$ and replace the image pixel in the anchor point position with that maximal value. As you can
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deduce, this maximizing operation causes bright regions within an image to "grow" (therefore the
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name *dilation*). Take as an example the image above. Applying dilation we can get:
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![image](images/Morphology_1_Tutorial_Theory_Dilation.png)
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The background (bright) dilates around the black regions of the letter.
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### Erosion
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- This operation is the sister of dilation. What this does is to compute a local minimum over the
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area of the kernel.
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- As the kernel \f$B\f$ is scanned over the image, we compute the minimal pixel value overlapped by
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\f$B\f$ and replace the image pixel under the anchor point with that minimal value.
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- Analagously to the example for dilation, we can apply the erosion operator to the original image
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(shown above). You can see in the result below that the bright areas of the image (the
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background, apparently), get thinner, whereas the dark zones (the "writing") gets bigger.
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![image](images/Morphology_1_Tutorial_Theory_Erosion.png)
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Code
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----
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This tutorial code's is shown lines below. You can also download it from
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[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/ImgProc/Morphology_1.cpp)
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@code{.cpp}
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#include "opencv2/imgproc.hpp"
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#include "opencv2/highgui.hpp"
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#include "highgui.h"
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#include <stdlib.h>
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#include <stdio.h>
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using namespace cv;
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/// Global variables
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Mat src, erosion_dst, dilation_dst;
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int erosion_elem = 0;
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int erosion_size = 0;
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int dilation_elem = 0;
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int dilation_size = 0;
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int const max_elem = 2;
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int const max_kernel_size = 21;
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/* Function Headers */
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void Erosion( int, void* );
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void Dilation( int, void* );
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/* @function main */
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int main( int argc, char** argv )
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{
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/// Load an image
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src = imread( argv[1] );
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if( !src.data )
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{ return -1; }
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/// Create windows
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namedWindow( "Erosion Demo", WINDOW_AUTOSIZE );
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namedWindow( "Dilation Demo", WINDOW_AUTOSIZE );
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cvMoveWindow( "Dilation Demo", src.cols, 0 );
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/// Create Erosion Trackbar
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createTrackbar( "Element:\n 0: Rect \n 1: Cross \n 2: Ellipse", "Erosion Demo",
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&erosion_elem, max_elem,
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Erosion );
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createTrackbar( "Kernel size:\n 2n +1", "Erosion Demo",
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&erosion_size, max_kernel_size,
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Erosion );
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/// Create Dilation Trackbar
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createTrackbar( "Element:\n 0: Rect \n 1: Cross \n 2: Ellipse", "Dilation Demo",
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&dilation_elem, max_elem,
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Dilation );
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createTrackbar( "Kernel size:\n 2n +1", "Dilation Demo",
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&dilation_size, max_kernel_size,
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Dilation );
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/// Default start
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Erosion( 0, 0 );
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Dilation( 0, 0 );
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waitKey(0);
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return 0;
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}
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/* @function Erosion */
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void Erosion( int, void* )
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{
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int erosion_type;
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if( erosion_elem == 0 ){ erosion_type = MORPH_RECT; }
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else if( erosion_elem == 1 ){ erosion_type = MORPH_CROSS; }
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else if( erosion_elem == 2) { erosion_type = MORPH_ELLIPSE; }
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Mat element = getStructuringElement( erosion_type,
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Size( 2*erosion_size + 1, 2*erosion_size+1 ),
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Point( erosion_size, erosion_size ) );
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/// Apply the erosion operation
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erode( src, erosion_dst, element );
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imshow( "Erosion Demo", erosion_dst );
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}
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/* @function Dilation */
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void Dilation( int, void* )
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{
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int dilation_type;
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if( dilation_elem == 0 ){ dilation_type = MORPH_RECT; }
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else if( dilation_elem == 1 ){ dilation_type = MORPH_CROSS; }
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else if( dilation_elem == 2) { dilation_type = MORPH_ELLIPSE; }
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Mat element = getStructuringElement( dilation_type,
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Size( 2*dilation_size + 1, 2*dilation_size+1 ),
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Point( dilation_size, dilation_size ) );
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/// Apply the dilation operation
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dilate( src, dilation_dst, element );
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imshow( "Dilation Demo", dilation_dst );
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}
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@endcode
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Explanation
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-----------
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1. Most of the stuff shown is known by you (if you have any doubt, please refer to the tutorials in
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previous sections). Let's check the general structure of the program:
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- Load an image (can be RGB or grayscale)
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- Create two windows (one for dilation output, the other for erosion)
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- Create a set of 02 Trackbars for each operation:
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- The first trackbar "Element" returns either **erosion_elem** or **dilation_elem**
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- The second trackbar "Kernel size" return **erosion_size** or **dilation_size** for the
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corresponding operation.
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- Every time we move any slider, the user's function **Erosion** or **Dilation** will be
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called and it will update the output image based on the current trackbar values.
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Let's analyze these two functions:
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2. **erosion:**
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@code{.cpp}
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/* @function Erosion */
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void Erosion( int, void* )
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{
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int erosion_type;
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if( erosion_elem == 0 ){ erosion_type = MORPH_RECT; }
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else if( erosion_elem == 1 ){ erosion_type = MORPH_CROSS; }
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else if( erosion_elem == 2) { erosion_type = MORPH_ELLIPSE; }
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Mat element = getStructuringElement( erosion_type,
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Size( 2*erosion_size + 1, 2*erosion_size+1 ),
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Point( erosion_size, erosion_size ) );
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/// Apply the erosion operation
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erode( src, erosion_dst, element );
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imshow( "Erosion Demo", erosion_dst );
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}
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@endcode
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- The function that performs the *erosion* operation is @ref cv::erode . As we can see, it
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receives three arguments:
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- *src*: The source image
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- *erosion_dst*: The output image
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- *element*: This is the kernel we will use to perform the operation. If we do not
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specify, the default is a simple @ref cv::3x3\` matrix. Otherwise, we can specify its
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shape. For this, we need to use the function
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get_structuring_element:\`getStructuringElement :
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@code{.cpp}
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Mat element = getStructuringElement( erosion_type,
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Size( 2*erosion_size + 1, 2*erosion_size+1 ),
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Point( erosion_size, erosion_size ) );
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@endcode
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We can choose any of three shapes for our kernel:
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- Rectangular box: MORPH_RECT
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- Cross: MORPH_CROSS
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- Ellipse: MORPH_ELLIPSE
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Then, we just have to specify the size of our kernel and the *anchor point*. If not
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specified, it is assumed to be in the center.
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- That is all. We are ready to perform the erosion of our image.
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@note Additionally, there is another parameter that allows you to perform multiple erosions
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(iterations) at once. We are not using it in this simple tutorial, though. You can check out the
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Reference for more details.
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1. **dilation:**
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The code is below. As you can see, it is completely similar to the snippet of code for **erosion**.
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Here we also have the option of defining our kernel, its anchor point and the size of the operator
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to be used.
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@code{.cpp}
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/* @function Dilation */
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void Dilation( int, void* )
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{
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int dilation_type;
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if( dilation_elem == 0 ){ dilation_type = MORPH_RECT; }
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else if( dilation_elem == 1 ){ dilation_type = MORPH_CROSS; }
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else if( dilation_elem == 2) { dilation_type = MORPH_ELLIPSE; }
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Mat element = getStructuringElement( dilation_type,
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Size( 2*dilation_size + 1, 2*dilation_size+1 ),
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Point( dilation_size, dilation_size ) );
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/// Apply the dilation operation
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dilate( src, dilation_dst, element );
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imshow( "Dilation Demo", dilation_dst );
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}
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@endcode
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Results
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-------
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- Compile the code above and execute it with an image as argument. For instance, using this image:
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![image](images/Morphology_1_Tutorial_Original_Image.jpg)
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We get the results below. Varying the indices in the Trackbars give different output images,
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naturally. Try them out! You can even try to add a third Trackbar to control the number of
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iterations.
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![image](images/Morphology_1_Tutorial_Cover.jpg)
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