OpenCV  3.2.0
Open Source Computer Vision
Creating Bounding boxes and circles for contours

.2.0+dfsg_doc_tutorials_imgproc_shapedescriptors_bounding_rects_circles_bounding_rects_circles

Goal

In this tutorial you will learn how to:

Theory

Code

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

#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( " Threshold:", "Source", &thresh, max_thresh, thresh_callback );
thresh_callback( 0, 0 );
waitKey(0);
return(0);
}
void thresh_callback(int, void* )
{
Mat threshold_output;
vector<vector<Point> > contours;
vector<Vec4i> hierarchy;
threshold( src_gray, threshold_output, thresh, 255, THRESH_BINARY );
findContours( threshold_output, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0) );
vector<vector<Point> > contours_poly( contours.size() );
vector<Rect> boundRect( contours.size() );
vector<Point2f>center( contours.size() );
vector<float>radius( contours.size() );
for( size_t i = 0; i < contours.size(); i++ )
{
approxPolyDP( Mat(contours[i]), contours_poly[i], 3, true );
boundRect[i] = boundingRect( Mat(contours_poly[i]) );
minEnclosingCircle( contours_poly[i], center[i], radius[i] );
}
Mat drawing = Mat::zeros( threshold_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_poly, (int)i, color, 1, 8, vector<Vec4i>(), 0, Point() );
rectangle( drawing, boundRect[i].tl(), boundRect[i].br(), color, 2, 8, 0 );
circle( drawing, center[i], (int)radius[i], color, 2, 8, 0 );
}
namedWindow( "Contours", WINDOW_AUTOSIZE );
imshow( "Contours", drawing );
}

Explanation

The main function is rather simple, as follows from the comments we do the following:

  1. Open the image, convert it into grayscale and blur it to get rid of the noise.
    src = imread( argv[1], IMREAD_COLOR );
    cvtColor( src, src_gray, COLOR_BGR2GRAY );
    blur( src_gray, src_gray, Size(3,3) );
  2. Create a window with header "Source" and display the source file in it.
    const char* source_window = "Source";
    namedWindow( source_window, WINDOW_AUTOSIZE );
    imshow( source_window, src );
  3. Create a trackbar on the source_window and assign a callback function to it In general callback functions are used to react to some kind of signal, in our case it's trackbar's state change.
    createTrackbar( " Threshold:", "Source", &thresh, max_thresh, thresh_callback );
  4. Explicit one-time call of thresh_callback is necessary to display the "Contours" window simultaniously with the "Source" window.
    thresh_callback( 0, 0 );
  5. Wait for user to close the windows.
    waitKey(0);

The callback function thresh_callback does all the interesting job.

  1. Writes to threshold_output the threshold of the grayscale picture (you can check out about thresholding here).
    threshold( src_gray, threshold_output, thresh, 255, THRESH_BINARY );
  2. Finds contours and saves them to the vectors contour and hierarchy.
    findContours( threshold_output, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0) );
  3. For every found contour we now apply approximation to polygons with accuracy +-3 and stating that the curve must me closed.

    After that we find a bounding rect for every polygon and save it to boundRect.

    At last we find a minimum enclosing circle for every polygon and save it to center and radius vectors.

    for( size_t i = 0; i < contours.size(); i++ )
    {
    approxPolyDP( Mat(contours[i]), contours_poly[i], 3, true );
    boundRect[i] = boundingRect( Mat(contours_poly[i]) );
    minEnclosingCircle( contours_poly[i], center[i], radius[i] );
    }

    We found everything we need, all we have to do is to draw.

  4. Create new Mat of unsigned 8-bit chars, filled with zeros. It will contain all the drawings we are going to make (rects and circles).
    Mat drawing = Mat::zeros( threshold_output.size(), CV_8UC3 );
  5. For every contour: pick a random color, draw the contour, the bounding rectangle and the minimal enclosing circle with it,
    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_poly, (int)i, color, 1, 8, vector<Vec4i>(), 0, Point() );
    rectangle( drawing, boundRect[i].tl(), boundRect[i].br(), color, 2, 8, 0 );
    circle( drawing, center[i], (int)radius[i], color, 2, 8, 0 );
    }
  6. Display the results: create a new window "Contours" and show everything we added to drawings on it.
    namedWindow( "Contours", WINDOW_AUTOSIZE );
    imshow( "Contours", drawing );

Result

Here it is:

imgproc.hpp
cv::IMREAD_COLOR
@ IMREAD_COLOR
If set, always convert image to the 3 channel BGR color image.
Definition: imgcodecs.hpp:67
cv::THRESH_BINARY
@ THRESH_BINARY
Definition: imgproc.hpp:329
cv::Mat::zeros
static MatExpr zeros(int rows, int cols, int type)
Returns a zero array of the specified size and type.
cv::cvtColor
void cvtColor(InputArray src, OutputArray dst, int code, int dstCn=0)
Converts an image from one color space to another.
cv::minEnclosingCircle
void minEnclosingCircle(InputArray points, Point2f &center, float &radius)
Finds a circle of the minimum area enclosing a 2D point set.
cv::threshold
double threshold(InputArray src, OutputArray dst, double thresh, double maxval, int type)
Applies a fixed-level threshold to each array element.
cv::waitKey
int waitKey(int delay=0)
Waits for a pressed key.
highgui.hpp
cv::namedWindow
void namedWindow(const String &winname, int flags=WINDOW_AUTOSIZE)
Creates a window.
cv::Scalar_< double >
cv::Size
Size2i Size
Definition: types.hpp:315
cv::rectangle
void rectangle(InputOutputArray img, Point pt1, Point pt2, const Scalar &color, int thickness=1, int lineType=LINE_8, int shift=0)
Draws a simple, thick, or filled up-right rectangle.
cv::imread
Mat imread(const String &filename, int flags=IMREAD_COLOR)
Loads an image from a file.
cv::COLOR_BGR2GRAY
@ COLOR_BGR2GRAY
convert between RGB/BGR and grayscale, color conversions
Definition: imgproc.hpp:538
CV_8UC3
#define CV_8UC3
Definition: interface.h:84
cv::Mat::size
MatSize size
Definition: mat.hpp:1978
imgcodecs.hpp
cv::imshow
void imshow(const String &winname, InputArray mat)
Displays an image in the specified window.
cv::approxPolyDP
void approxPolyDP(InputArray curve, OutputArray approxCurve, double epsilon, bool closed)
Approximates a polygonal curve(s) with the specified precision.
cv::boundingRect
Rect boundingRect(InputArray points)
Calculates the up-right bounding rectangle of a point set.
cv::Scalar
Scalar_< double > Scalar
Definition: types.hpp:606
cv::RNG
Random Number Generator.
Definition: core.hpp:2690
cv::drawContours
void drawContours(InputOutputArray image, InputArrayOfArrays contours, int contourIdx, const Scalar &color, int thickness=1, int lineType=LINE_8, InputArray hierarchy=noArray(), int maxLevel=INT_MAX, Point offset=Point())
Draws contours outlines or filled contours.
cv::blur
void blur(InputArray src, OutputArray dst, Size ksize, Point anchor=Point(-1,-1), int borderType=BORDER_DEFAULT)
Blurs an image using the normalized box filter.
cv::Point
Point2i Point
Definition: types.hpp:183
cv::Mat
n-dimensional dense array class
Definition: mat.hpp:741
i
for i
Definition: modelConvert.m:63
cv::createTrackbar
int createTrackbar(const String &trackbarname, const String &winname, int *value, int count, TrackbarCallback onChange=0, void *userdata=0)
Creates a trackbar and attaches it to the specified window.
cv
Definition: affine.hpp:52
cv::WINDOW_AUTOSIZE
@ WINDOW_AUTOSIZE
the user cannot resize the window, the size is constrainted by the image displayed.
Definition: highgui.hpp:184
cv::CHAIN_APPROX_SIMPLE
@ CHAIN_APPROX_SIMPLE
Definition: imgproc.hpp:448
cv::findContours
void findContours(InputOutputArray image, OutputArrayOfArrays contours, OutputArray hierarchy, int mode, int method, Point offset=Point())
Finds contours in a binary image.
cv::RETR_TREE
@ RETR_TREE
Definition: imgproc.hpp:436
cv::datasets::circle
@ circle
Definition: gr_skig.hpp:62
cv::circle
void circle(InputOutputArray img, Point center, int radius, const Scalar &color, int thickness=1, int lineType=LINE_8, int shift=0)
Draws a circle.