[OpenCV Tutorial] $10 -Image Moments

Goal

In this tutorial you will learn how to:

• Use the OpenCV function cv::moments
• Use the OpenCV function cv::contourArea
• Use the OpenCV function cv::arcLength

Theory

Code

This tutorial code's is shown lines below. You can also download it from here

#include "opencv2/imgcodecs.hpp"

#include "opencv2/highgui.hpp"

#include "opencv2/imgproc.hpp"

#include <iostream>

using namespace cv;

using namespace std;

Mat src; Mat src_gray;

int thresh = 100;

int max_thresh = 255;

RNG rng(12345);

void thresh_callback(int, void* );

int main( int, char** argv )

{

src = imread( argv[1], IMREAD_COLOR );

cvtColor( src, src_gray, COLOR_BGR2GRAY );

blur( src_gray, src_gray, Size(3,3) );

const char* source_window = "Source";

namedWindow( source_window, WINDOW_AUTOSIZE );

imshow( source_window, src );

createTrackbar( " Canny thresh:", "Source", &thresh, max_thresh, thresh_callback );

thresh_callback( 0, 0 );

waitKey(0);

return(0);

}

void thresh_callback(int, void* )

{

Mat canny_output;

vector<vector<Point> > contours;

vector<Vec4i> hierarchy;

Canny( src_gray, canny_output, thresh, thresh*2, 3 );

findContours( canny_output, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0) );

vector<Moments> mu(contours.size() );

for( size_t i = 0; i < contours.size(); i++ )

{ mu[i] = moments( contours[i], false ); }

vector<Point2f> mc( contours.size() );

for( size_t i = 0; i < contours.size(); i++ )

{ mc[i] = Point2f( static_cast<float>(mu[i].m10/mu[i].m00) , static_cast<float>(mu[i].m01/mu[i].m00) ); }

Mat drawing = Mat::zeros( canny_output.size(), CV_8UC3 );

for( size_t i = 0; i< contours.size(); i++ )

{

Scalar color = Scalar( rng.uniform(0, 255), rng.uniform(0,255), rng.uniform(0,255) );

drawContours( drawing, contours, (int)i, color, 2, 8, hierarchy, 0, Point() );

circle( drawing, mc[i], 4, color, -1, 8, 0 );

}

namedWindow( "Contours", WINDOW_AUTOSIZE );

imshow( "Contours", drawing );

printf("\t Info: Area and Contour Length \n");

for( size_t i = 0; i< contours.size(); i++ )

{

printf(" * Contour[%d] - Area (M_00) = %.2f - Area OpenCV: %.2f - Length: %.2f \n", (int)i, mu[i].m00, contourArea(contours[i]), arcLength( contours[i], true ) );

Scalar color = Scalar( rng.uniform(0, 255), rng.uniform(0,255), rng.uniform(0,255) );

drawContours( drawing, contours, (int)i, color, 2, 8, hierarchy, 0, Point() );

circle( drawing, mc[i], 4, color, -1, 8, 0 );

}

}

Explanation

Canny() [1/2]

void cv::Canny	(	InputArray	image,
		OutputArray	edges,
		double	threshold1,
		double	threshold2,
		int	apertureSize = 3,
		bool	L2gradient = false
	)

Finds edges in an image using the Canny algorithm [26] .

The function finds edges in the input image image and marks them in the output map edges using the Canny algorithm. The smallest value between threshold1 and threshold2 is used for edge linking. The largest value is used to find initial segments of strong edges. See http://en.wikipedia.org/wiki/Canny_edge_detector

Parameters

image	8-bit input image.
edges	output edge map; single channels 8-bit image, which has the same size as image .
threshold1	first threshold for the hysteresis procedure.
threshold2	second threshold for the hysteresis procedure.
apertureSize	aperture size for the Sobel operator.
L2gradient	a flag, indicating whether a more accurate L2 norm =(dI/dx)2+(dI/dy)2−−−−−−−−−−−−−−−−√ should be used to calculate the image gradient magnitude ( L2gradient=true ), or whether the default L1 norm =|dI/dx|+|dI/dy| is enough ( L2gradient=false ).

Result

Here it is: