Reputation: 49
I've been reading about opencv and I've been doing some exercises, in this case I want to perform an image equalization, I have implemented the following code, but when I execute it I get the following error:
"Segmentation fault (core dumped)"
So I have no idea what is due.
The formula I am trying to use is the following:
The code is the following:
#include <opencv2/opencv.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <stdio.h>
using namespace cv;
using namespace std;
void equalization(cv::Mat &image,cv::Mat &green, int m) {
Mat eqIm;
int nl= image.rows; // number of lines
int nc= image.cols * image.channels();
for (int j=0; j<nl; j++) {
uchar* data= image.ptr<uchar>(j);
uchar* data2= green.ptr<uchar>(j);
uchar* eqIm= green.ptr<uchar>(j);
for (int i=0; i<nc; i++) {
eqIm[i]= data[i]+m-data2[i];
}
}
cv::imshow("Image",eqIm);
imwrite("eqIm.png",eqIm);
}
float mean(cv::Mat &image){
cv:Scalar tempVal = mean( image );
float myMAtMean = tempVal.val[0];
cout << "The value is " << myMAtMean;
}
int main(int argc, char** argv ){
Mat dst;
Mat image= cv::imread("img.jpg");
Mat green= cv::imread("green.jpg");
cv::imshow("Image",image);
float m= mean(image);
equalization(image,green,m);
cv::namedWindow("Image");
cv::imshow("Image",image);
imwrite("equalizated.png",dst);
waitKey(0);
return 0;
}
and the image "Equalization.png" that is written contains nothing
Upvotes: 1
Views: 90
Reputation: 663
You never initialized Mat eqIm
, so when you do cv::imshow("Image", eqIm);
imwrite("eqIm.png", eqIm);
there is nothing in the mat. https://docs.opencv.org/2.4/doc/tutorials/core/mat_the_basic_image_container/mat_the_basic_image_container.html
Also, I should note that you have 2 variables of eqIm
. That may be part of the confusion.
One last thing, in your mean
function, you may end up with a recursive function. You should specify what mean function you are using in the mean function you create, i.e.
float mean(cv::Mat &image) {
cv:Scalar tempVal = cv::mean(image);
float myMAtMean = tempVal.val[0];
cout << "The value is " << myMAtMean;
return myMAtMean;
}
The following is something closer to what you are looking for in your equalization function.
void equalization(cv::Mat &image, cv::Mat &green, int m) {
Mat eqIm(image.rows,image.cols,image.type());
int nl = image.rows; // number of lines
int nc = image.cols * image.channels();
for (int j = 0; j<nl; j++) {// j is each row
for (int ec = 0; ec < nc; ec++) {//ec is each col and channels
eqIm.data[j*image.cols*image.channels() + ec] = image.data[j*image.cols*image.channels() + ec] + m - green.data[j*image.cols*image.channels() + ec];
}
}
cv::imshow("Image", eqIm);
imwrite("eqIm.png", eqIm);
}
I do j*image.cols*image.channels()
to step through the entire size of j lines (the number of columns times the number of channels per pixel).
Upvotes: 2