How to get pixel value from the contoured image with mask? - c++

Question

I tried to extract average pixel values (R, G, B) from the contoured image. However, my problem is when I applied the code below, something strange values were observed.
int main(){
cv::Mat star = imread("C:\\Users\\PC\\Desktop\\star\\starcircle.png");
cv::Mat mask = cv::Mat::zeros(star.rows, star.cols, CV_8UC1);
cv::Mat frame;
double b, g, r = 0.0;
cv::imshow("Original", star);
cv::cvtColor(star, frame, CV_BGR2HSV);
cv::inRange(frame, cv::Scalar(29, 220, 220), cv::Scalar(30, 255, 255), mask);
cv::imshow("mask", mask);
cv::Mat result = cv::Mat(star.rows, star.cols, CV_8UC1, star.type());
result.setTo(cv::Scalar(0, 0, 0));
star.copyTo(result, mask);
cv::Scalar temp = mean(mask);
cout << "avg_R: " << temp[2] << " \n"; // red value
cout << "avg_G: " << temp[1] << " \n"; // green value
cout << "avg_B: " << temp[0] << " \n\n"; // blue value
cv::imshow("result", result);
cv::waitKey(-1);
return 0;
}
And I got the correct images for the result like below.
I want to read pixel values only for yellow part, not for outside of mask.
And I have another code for read out pixel values in the yellow parts, but it showed the same result.
int main(){
cv::Mat star = imread("C:\\Users\\PC\\Desktop\\star\\starcircle.png");
cv::Mat mask = cv::Mat::zeros(star.rows, star.cols, CV_8UC1);
cv::Mat frame;
double b, g, r = 0.0;
cv::imshow("Original", star);
cv::cvtColor(star, frame, CV_BGR2HSV);
cv::inRange(frame, cv::Scalar(29, 220, 220), cv::Scalar(30, 255, 255), mask);
cv::imshow("mask", mask);
cv::Mat result = cv::Mat(star.rows, star.cols, CV_8UC1, star.type());
result.setTo(cv::Scalar(0, 0, 0));
star.copyTo(result, mask);
int hei = star.rows;
int wid = star.cols;
int corow = hei * wid;
double b, g, r = 0.0;
for (int x = 0; x < hei; x++) {
for (int y = 0; y < wid; y++) {
if (mask.at<unsigned char>(x, y) > 0) {
b += result.at<Vec3b>(x, y)[0];
g += result.at<Vec3b>(x, y)[1];
r += result.at<Vec3b>(x, y)[2];
}
else {
}
}
}
cout << "$$ Red(R), Green(G), Blue(B) $$" << " \n\n";
cout << "avg_R: " << r / corow << " \n"; // red value
cout << "avg_G: " << g / corow << " \n"; // green value
cout << "avg_B: " << b / corow << " \n\n"; // blue value
}
Please help me to revise the error.
Thank you in advance.

Answer 1

A few things:
Your variables names and Mat types are at least confusing. Use proper names for the variables, and use Mat_<T> whenever possible (I'd say always).
To get the mean you should divide by the number of pixels in the mask, not by total number of pixels.
you should consider using cv::mean
you need cv::waitKey() to actually see your cv::imshow
Check the code:
#include <opencv2\opencv.hpp>
int main()
{
cv::Mat3b star = cv::imread("path/to/image");
cv::imshow("Original", star);
cv::Mat3b hsv;
cv::cvtColor(star, hsv, cv::COLOR_BGR2HSV);
cv::Mat1b mask;
cv::inRange(hsv, cv::Scalar(29, 220, 220), cv::Scalar(30, 255, 255), mask);
cv::imshow("mask", mask);
// Change to 'false' to see how to use the 'cv::mask' approach
if (true)
{
double blue, green, red = 0.0;
int counter = 0;
for (int r = 0; r < star.rows; r++)
{
for (int c = 0; c < star.cols; c++)
{
if (mask(r, c) > 0)
{
++counter;
blue += star(r, c)[0];
green += star(r, c)[1];
red += star(r, c)[2];
}
}
}
// Avoid division by 0
if (counter > 0)
{
blue /= counter;
green /= counter;
red /= counter;
}
std::cout << "$$ Red(R), Green(G), Blue(B) $$" << " \n\n";
std::cout << "avg_R: " << red << " \n";
std::cout << "avg_G: " << green << " \n";
std::cout << "avg_B: " << blue << " \n\n";
}
else
{
cv::Scalar mean_value = cv::mean(star, mask);
double blue = mean_value[0];
double green = mean_value[1];
double red = mean_value[2];
std::cout << "$$ Red(R), Green(G), Blue(B) $$" << " \n\n";
std::cout << "avg_R: " << red << " \n"; // red value
std::cout << "avg_G: " << green << " \n"; // green value
std::cout << "avg_B: " << blue << " \n\n"; // blue value
}
cv::waitKey();
}

Answer 2

I see several errors in your code:
cv::Mat result = cv::Mat(star.rows, star.cols, CV_8UC1, star.type());
result.setTo(cv::Scalar(0, 0, 0));
star.copyTo(result, mask);
cv::Scalar temp = mean(mask);
If result is of type CV_8UC1 then you copyTo one channel? (The C1 from CV_8U means one channel). Then you use star.type() where the value to be set should be... You do also the mean to a mask, which will give you a scalar with only one channel set, since it is a binary image of type CV_8UC1... for it to work, it should be:
cv::Mat result = cv::Mat(star.rows, star.cols, star.type(), cv::Scalar::all(0));
star.copyTo(result, mask);
cv::Scalar temp = mean(result);
For the second part, it is ok to add it like that, however if you have not fixed the previous error... I think it should give you segmentation error at some point or weird results if you are lucky. Finally the result part you have this:
cout << "$$ Red(R), Green(G), Blue(B) $$" << " \n\n";
cout << "avg_R: " << r / corow << " \n"; // red value
cout << "avg_G: " << g / corow << " \n"; // green value
cout << "avg_B: " << b / corow << " \n\n"; // blue value
but corow should be the non zero points of the mask, so it should be:
corow = cv::countNonZero(mask);
cout << "$$ Red(R), Green(G), Blue(B) $$" << " \n\n";
cout << "avg_R: " << r / corow << " \n"; // red value
cout << "avg_G: " << g / corow << " \n"; // green value
cout << "avg_B: " << b / corow << " \n\n"; // blue value
if not it will give you a smaller number, since it is divided with a a number that includes the black points which do not contribute.
As an extra note, you should use more OpenCV functions... in this case cv::mean does the same thing, if not you can simplify it with sum and divide like:
cv::Scalar summed = cv::sum(result);
cv::Scalar mean = summed / static_cast<double>(cv::countNonZero(mask));
std::cout << "$$ Red(R), Green(G), Blue(B) $$" << std::endl << std::endl;
std::cout << "avg_R: " << mean[2] << std::endl; // red value
std::cout << "avg_G: " << mean[1] << std::endl; // green value
std::cout << "avg_B: " << mean[0] << std::endl << std::endl; // blue value
This is assuming you did the star.copyTo(result, mask); line

Answer 3

Read about cv::Mat::at: first row, second col. Not (x, y)!
See you on cv::mean: it can work with mask.
Right initialization: double b = 0.0, g = 0.0, r = 0.0;
int corow = 0; And inside loop ++corow if mask > 0.