Image Morphology using OpenCV

1. Erosion

Erosion

generally decreases the sizes of objects and removes small anomalies by subtracting objects with a radius smaller than the structuring element.

void cvErode( const CvArr* src, CvArr* dst,
IplConvKernel*element=NULL, int iterations=1 );

The function describes:
src
-Source image
dst
-Destination image
element
-Structuring element used for erosion. If it is NULL, a 3×3 rectangular
structuring element is used
iterations
-Number of times erosion is applied

#include "stdafx.h"
#include <cv.h>
#include <cxcore.h>
#include <highgui.h>

int _tmain(int argc, _TCHAR* argv[])
{

IplImage *img = cvLoadImage("Image2.png");
IplImage *dest =cvCreateImage(cvSize(img->width,img->height),8,3);
IplImage *temp =cvCreateImage(cvSize(img->width,img->height),8,3);

cvErode(img,dest,NULL,2);

cvNamedWindow("Image:");
cvNamedWindow("Destination:");

cvShowImage("Image:", img);
cvShowImage("Destination:", dest);

cvWaitKey(0);

cvDestroyWindow("Image:");
cvDestroyWindow("Destination:");

cvReleaseImage(&img);
cvReleaseImage(&dest);
return 0;
}

2. Dilation

Dilation

generally increases the sizes of objects, filling in holes and broken areas, and connecting areas that are separated by spaces smaller than the size of the structuring element.

void cvDilate( const CvArr* src, CvArr* dst, IplConvKernel*
element=NULL, int iterations=1 );

#include "stdafx.h"
#include <cv.h>
#include <cxcore.h>
#include <highgui.h>

int _tmain(int argc, _TCHAR* argv[])
{

IplImage *img = cvLoadImage("Image2.png");
IplImage *dest =cvCreateImage(cvSize(img->width,img->height),8,3);
IplImage *temp =cvCreateImage(cvSize(img->width,img->height),8,3);

cvDilate(img,dest,NULL,2);

cvNamedWindow("Image:");
cvNamedWindow("Destination:");

cvShowImage("Image:", img);
cvShowImage("Destination:", dest);

cvWaitKey(0);

cvDestroyWindow("Image:");
cvDestroyWindow("Destination:");

cvReleaseImage(&img);
cvReleaseImage(&dest);
return 0;
}


3. MorphologyEx 
This function performs advanced morphological transformations, which enables composite operations such as Opening, Closing, Morphological Gradient, Top Hat and Black Hat. The one function that lets you do all this is:

void cvMorphologyEx( const CvArr* src, CvArr* dst, CvArr* temp,

IplConvKernel* element, int operation, int iterations=1 );
The function describes:

src

-Source image

dst

-Destination image

temp

-Temporary image, required in some cases

element

-Structuring element

operation

-Type of morphological operation, one of:

CV_MOP_OPEN - opening

CV_MOP_CLOSE - closing

CV_MOP_GRADIENT - morphological gradient

CV_MOP_TOPHAT - "top hat"

CV_MOP_BLACKHAT - "black hat"

iterations

-Number of times erosion and dilation are applied
#include "stdafx.h"
#include <cv.h>
#include <cxcore.h>
#include <highgui.h>

int _tmain(int argc, _TCHAR* argv[])
{

IplImage *img = cvLoadImage("Image2.png");
IplImage *dest =cvCreateImage(cvSize(img->width,img->height),8,3);
IplImage *temp =cvCreateImage(cvSize(img->width,img->height),8,3);

cvMorphologyEx(img,dest,temp,structure,MOP_CLOSE,1);
cvNamedWindow("Image:");
cvNamedWindow("Destination:");

cvShowImage("Image:", img);
cvShowImage("Destination:", dest);

cvWaitKey(0);

cvDestroyWindow("Image:");
cvDestroyWindow("Destination:");

cvReleaseImage(&img);
cvReleaseImage(&dest);
return 0;
}

			

			
			
		
 

		
			

Edge Detection with OpenCV

Edge detection is considered as the most common approach for detecting meaningful discontinuities in the grey- level.

1. Sobel Operator

void cvSobel( const CvArr* src, CvArr* dst, int xorder, int yorder,
int aperture_size=3 );

Parameters:
src – Source image
dst – Destination image
xorder – First Order derivative in x direction
yorder – First Order derivative in y direction
apertureSize – Size of the extended Sobel kernel, must be 1, 3, 5 or 7

The function is called with (xorder=1, yorder=0, aperture_size=3)
|-1 0 1|
|-2 0 2|
|-1 0 1|

and (xorder=0, yorder=1, aperture_size=3)

|-1 -2 -1|
| 0 0 0|
| 1 2 1|

#include <cv.h>
#include <cxcore.h>
#include <highgui.h>

int _tmain(int argc, _TCHAR* argv[])
{

IplImage *img = cvLoadImage("building.jpg");

IplImage *gray;
IplImage *sobelX;
IplImage *sobelY;
IplImage *tempX;
IplImage *tempY;

gray =cvCreateImage(cvSize(img->width,img->height),8,1);

cvCvtColor(img,gray,CV_RGB2GRAY);
if(!img)
{
printf("Error :coudn't open the image file.\n");
return 1;
}

sobelX =cvCreateImage(cvSize(img->width,img->height),8,1);
sobelY =cvCreateImage(cvSize(img->width,img->height),8,1);

// Create Temp Images
tempX =cvCreateImage(cvSize(img->width,img->height),IPL_DEPTH_16S,1);
tempY =cvCreateImage(cvSize(img->width,img->height),IPL_DEPTH_16S,1);

cvSobel(gray,tempX,1,0,3);
cvSobel(gray,tempY,0,1,3);

// Convert to the Absolute Value
cvConvertScaleAbs(tempX,sobelX,1,0);
cvConvertScaleAbs(tempY,sobelY,1,0);

cvNamedWindow("Image:",1);
cvShowImage("Image:", img);

cvNamedWindow("Image:",1);
cvShowImage("Gray:", gray);

cvNamedWindow("sobelx:",1);
cvNamedWindow("sobely:",1);

cvShowImage("sobelx:", sobelX);
cvShowImage("sobely:", sobelY);

cvWaitKey(0);

cvDestroyWindow("Image:");
cvDestroyWindow("Gray:");
cvDestroyWindow("sobelx:");
cvDestroyWindow("sobely:");

cvReleaseImage(&img);
cvReleaseImage(&gray);
cvReleaseImage(&sobelX);
cvReleaseImage(&sobelY);
return 0;
}

1. LaplacianOperator

The function calculates the Laplacian of the source image by filtering the image with the
following 3X3 aperture:

|-1 -1 -1|
| -1 8 -1|
|-1 -1 -1|

Use the following function to apply the Laplacian operator:

void cvLaplace(const CvArr* src, CvArr* dst, int apertureSize=3)

Parameters:
src – Source image
dst – Destination image
apertureSize – Size of the extended Sobel kernel

#include <cv.h>
#include <cxcore.h>
#include <highgui.h>

int _tmain(int argc, _TCHAR* argv[])
{
IplImage *img = cvLoadImage("building.jpg");

IplImage *gray;
IplImage *laplace;
IplImage *temp;


gray =cvCreateImage(cvSize(img->width,img->height),8,1);
cvCvtColor(img,gray,CV_RGB2GRAY);

temp =cvCreateImage(cvSize(img->width,img->height),IPL_DEPTH_16S,1);
laplace =cvCreateImage(cvSize(img->width,img->height),8,1);

IplImage *dst1=cvCreateImage(cvSize(img->width,img->height),8,1);

cvLaplace(gray,temp,3);
cvConvertScaleAbs(temp,laplace,1,0);

cvSmooth( laplace, dst1,CV_MEDIAN,3,3);

cvNamedWindow("Image:",1);
cvShowImage("Image:", img);

//cvNamedWindow("temp:",1);
cvNamedWindow("Laplace:",1);
cvNamedWindow("remove:",1);

cvShowImage("Laplace:", laplace);
cvShowImage("remove:", dst1);

cvWaitKey(0);

cvDestroyWindow("Image:");
cvDestroyWindow("Laplace:");
cvDestroyWindow("remove:");


//cvReleaseImage(&img);
cvReleaseImage(&laplace);
cvReleaseImage(&dst1);
return 0;
}

 

How to use Order Statistic Filters with OpenCV

Order Statistic Filters

Order Statistic filters are filters whose response is based on ordering/ranking the pixels
containing in the 3×3 window.
1. Median filter

The value of the centre pixel is replaced by the median value of its neighbourhood pixels. The median is taken after arranging the pixel values in ascending order and then taking the middle value. Use the following function,

void cvSmooth( const CvArr* src,
CvArr* dst,
int smoothtype=CV_MEDIAN,
int param1=3, int param2=3);

CV_MEDIAN (median blur) – finding median of param1×param1 neighborhood (the neighborhood is square).
2. Max filter
The max filter uses the maximum value of its neighbourhood pixels to replace the centre pixel value.

void cvDilate(const CvArr* src,
CvArr* dst,
IplConvKernel* element=NULL,
int iterations=1)

The function dilates the source image using the specified structuring element that determines the shape of a pixel neighborhood over which the maximum is taken. Image Understanding and Processing (OpenCV)

3. Minimum filter
The minimum filter uses the minimum value of its neighbourhood pixels to replace the centre pixel value.

void cvErode(const CvArr* src,
CvArr* dst,
IplConvKernel* element=NULL,
int iterations=1)

The function erodes the source image using the specified structuring element that determines the shape of a pixel neighborhood over which the minimum is taken.

Sample Code

#include "stdafx.h"
#include <cv.h>
#include <cxcore.h>
#include <highgui.h>

int _tmain(int argc, _TCHAR* argv[])
{

IplImage *img = cvLoadImage("apple noise.jpg");
IplImage *dst1=cvCreateImage(cvSize(img->width,img->height),8,3);

//cvSmooth(img,dst,CV_MEDIAN,3,3); Median Filter
//cvDilate(img,dst,NULL,1); Max Filter
//cvErode(img,dst,NULL,1); //Max FiltercvNamedWindow

cvNamedWindow("Image:");
cvShowImage("Image:", img);

cvNamedWindow("DST:");
cvShowImage("DST:", dst1);

cvWaitKey(0);

cvDestroyWindow("Image:");
cvReleaseImage(&img);

cvDestroyWindow("DST:");
cvReleaseImage(&dst1);

return 0;
}

 

Image Difference with OpenCV

First Image

Second Image

Image Difference

 #include "stdafx.h"
 #include<opencv\cv.h>
 #include<opencv\cxcore.h>
 #include<opencv\highgui.h>

int _tmain(int argc, _TCHAR* argv[])
 {

IplImage *first = cvLoadImage("C:\\Users\\first.jpg");
 IplImage *second = cvLoadImage("C:\\Users\\second.jpg");

IplImage *subImage;
 subImage = cvCloneImage(first);

cvAbsDiff(first,second,subImage);
 cvNamedWindow("Original:");
 cvShowImage("Original:", first);

cvNamedWindow("Modified:");
 cvShowImage("Modified:", second);

cvNamedWindow("Diff:");
 cvShowImage("Diff:", subImage);

cvWaitKey(0);
 cvDestroyWindow("Original:");
 cvReleaseImage(&first);
 cvDestroyWindow("Modified:");
 cvReleaseImage(&second);
 cvDestroyWindow("Diff:");
 cvReleaseImage(&subImage);
 return 0;

}