I have used canny edge detection and I have found the contours on an image I am trying to process. I want to find the five largest contours and then see whether or not there are contours within the five biggest contours in the image. Is this possible? I am new to OpenCV.
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You want to find if there are contours _inside_ the 5 largest? – Miki Oct 28 '15 at 21:24
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Yes. I have a picture of five bottles and I want to see whether the bottles have labels on them. The largest contours outline each bottle and if the bottle has a label there are additional contours inside it. Hope this makes sense. – Boots2014 Oct 28 '15 at 21:29
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Well, yes, it makes sense. Can you show what you tried so far? – Miki Oct 28 '15 at 21:36
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I'm away from my computer at the moment but my code was largely based on the source code from the open cv code here http://docs.opencv.org/doc/tutorials/imgproc/shapedescriptors/find_contours/find_contours.html I added a for loop in the function to find the largest contour. I'm not sure but I'm thinking I have to index the five largest contours somehow. – Boots2014 Oct 28 '15 at 23:25
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Posted an answer. You can see how to find the `N` largest contours, and how to get inner contours for each one. – Miki Oct 28 '15 at 23:46
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Wow thank you this is really helpful! – Boots2014 Oct 28 '15 at 23:48
1 Answers
11
You can find the N
largest contours checking their length. You should take care to pass to findContours
the parameter CHAIN_APPROX_NONE
for this to work properly.
You can then check inside each mask if there are other contours.
Image:
N = 5
largest contours, with inner contours for each one.
Code:
#include <opencv2\opencv.hpp>
#include <vector>
#include <numeric>
using namespace cv;
using namespace std;
int main()
{
Mat3b img = imread("path_to_image");
Mat1b gray;
cvtColor(img, gray, COLOR_BGR2GRAY);
Mat1b edges;
Canny(gray, edges, 200, 50);
vector<vector<Point>> contours;
findContours(edges.clone(), contours, RETR_EXTERNAL, CHAIN_APPROX_NONE);
vector<int> indices(contours.size());
iota(indices.begin(), indices.end(), 0);
sort(indices.begin(), indices.end(), [&contours](int lhs, int rhs) {
return contours[lhs].size() > contours[rhs].size();
});
int N = 5; // set number of largest contours
N = min(N, int(contours.size()));
Mat3b res = img.clone();
// Draw N largest contours
for (int i = 0; i < N; ++i)
{
Scalar color(rand() & 255, rand() & 255, rand() & 255);
Vec3b otherColor(color[2], color[0], color[1]);
drawContours(res, contours, indices[i], color, CV_FILLED);
// Create a mask for the contour
Mat1b res_mask(img.rows, img.cols, uchar(0));
drawContours(res_mask, contours, indices[i], Scalar(255), CV_FILLED);
// AND with edges
res_mask &= edges;
// remove larger contours
drawContours(res_mask, contours, indices[i], Scalar(0), 2);
for (int r = 0; r < img.rows; ++r)
{
for (int c = 0; c < img.cols; ++c)
{
if (res_mask(r, c))
{
res(r,c) = otherColor;
}
}
}
}
imshow("Image", img);
imshow("N largest contours", res);
waitKey();
return 0;
}

Miki
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