how to get Matrix(ROI) in openCV using by line that inclined - opencv

Question

I already tried to search about openCV ROI function, but All of them used rectangle roi function.
I want to get roi using by inclined line that get from hough transform function.
My situation is next :
I have multiple vertical lines(little inclined) that output from hough transform function.
i want to get image(Matrix) between vertical lines.
enter image description here
i want to get divided matrix in my image (For example, A image, B image, C image etc.. )
Is there ROI function that used line in openCV?
or
any another method?

Answer 1

I think you need to use contours to define your roi. If it is not a perfect square you can not use the ROI function, because this is always a perfect square (not even a rotated square)
int main()
{
enum hierIdx { H_NEXT = 0, H_PREVIOUS, H_FIRST_CHILD, H_PARENT };
cv::Mat img = cv::imread("example_image.jpg", cv::IMREAD_UNCHANGED);
// convert RGB to gray scale image
cv::Mat imgGrs;
cv::cvtColor(img, imgGrs, cv::COLOR_RGB2GRAY);
// because it was a .jpg the grey values are messed up
// we fix it by thresholding at 128
cv::threshold(imgGrs, imgGrs, 128, 255, cv::THRESH_BINARY);
imgGrs = ~imgGrs;
// now create contours (we need the hierarchy to find the inner shapes)
std::vector<std::vector<cv::Point> > contours;
std::vector<cv::Vec4i> hierarchy;
cv::findContours(imgGrs.clone(), contours, hierarchy, CV_RETR_TREE, CV_CHAIN_APPROX_SIMPLE);
//cv::drawContours(img, contours, -1, cv::Scalar(255, 0, 0), 1);
int iLen = (int)hierarchy.size();
int idxChild = -1;
// find first child of master
for (int i = 0; i < iLen; i++){
if (hierarchy[i][H_PARENT] < 0) {
idxChild = hierarchy[i][H_FIRST_CHILD];
break;
}
}
// used for erosion of mask
cv::Mat element = cv::getStructuringElement(cv::MORPH_ELLIPSE, cv::Size(3, 3));
while (idxChild >= 0)
{
// create image to use as mask for section
cv::Mat mask = cv::Mat::zeros(imgGrs.size(), CV_8U);
cv::drawContours(mask, contours, idxChild, cv::Scalar(255), CV_FILLED);
// make masker 1 pixel smaller so we wont see the outer contours
cv::erode(mask, mask, element);
// ok nu we create a singled out part we want
cv::Mat part = imgGrs & mask;
// Crop it to the AOI rectangle
cv::Rect aoi = cv::boundingRect(contours[idxChild]);
part = part(aoi);
// part is now the aoi image you asked for
// proceed to next AOI
idxChild = hierarchy[idxChild][H_NEXT];
}
return 0;
}