cv::Mat blobIdentification(cv::Mat image)
{
cv::Mat grayscaleImage;
cv::Mat imageOpening;
cv::Mat imageDifference;
cv::Mat imageThreshold;
cv::Mat meanImageDifference;
cv::Mat stdDevImageDifference;
// Morphological opening
cv::morphologyEx(image, imageOpening, cv::MORPH_OPEN, cv::getStructuringElement(cv::MORPH_RECT, cv::Size(9,9)));
// Get the threshold cutoff, generate the image difference
cv::subtract(image, imageOpening, imageDifference);
cv::meanStdDev(imageDifference, meanImageDifference, stdDevImageDifference);
double mean = meanImageDifference.at<double>(0, 0);
double stdev = stdDevImageDifference.at<double>(0, 0);
double threshold_value = mean + (3 * stdev);
imageThreshold = MatrixOperations::greaterThanValue((float)threshold_value, imageDifference);
// Only use pixels which pass the threshold from the cross correlation
cv::Mat grayscaleCrossCorrelation = crossCorrelateWithGaussian(image);
cv::bitwise_and(imageThreshold, grayscaleCrossCorrelation, grayscaleImage);
// Morphological close
cv::Mat closingElement = getStructuringElement(cv::MORPH_RECT, cv::Size(3,3));
cv::morphologyEx(grayscaleImage, grayscaleImage, cv::MORPH_CLOSE, closingElement);
grayscaleImage.convertTo(grayscaleImage, CV_8UC1);
return grayscaleImage;
}
cv::Mat blobIdentification(cv::Mat image, std::string debugPath)
{
//this is a hack, but it handles the different thresholds between this scope and Neil's scope
bool neilscope = false;
int thresholdMultiplier = 10;
if (image.rows==1944) {
neilscope = true;
thresholdMultiplier = 3;
std::cout << "running as Neilscope image\n";
}
//input image has been normalized
cv::Mat grayscaleImage;
cv::Mat imageOpening;
cv::Mat imageDifference;
cv::Mat imageThreshold;
cv::Mat meanImageDifference;
cv::Mat stdDevImageDifference;
// Get background image via morphological opening w/ 9x9 strel
//Q: use gaussianBlur instead?
cv::morphologyEx(image, imageOpening, cv::MORPH_OPEN, cv::getStructuringElement(cv::MORPH_RECT, cv::Size(9,9)));
//std::cout << "opened\n";
if (debugPath!="")
imwrite(debugPath + "/opened2-1.tif",imageOpening*255);
// Subtract background
cv::subtract(image, imageOpening, imageDifference);
if (debugPath!="")
imwrite(debugPath + "/subtracted2-2.tif",imageDifference*255);
//std::cout << "subtracted\n";
imageOpening.release(); //FBM
//TODO: bring all these parameters out to settings
//TODO: image mask
if (!neilscope)
{
cv::Mat img_mask(image.rows,image.cols, CV_8UC1);
img_mask = cv::Scalar(0);
for (int i = 800; i < 1800; i++) {
for (int j = 400; j < 1400; j++) {
img_mask.at<char>(i,j) = 1;
}
}
if (debugPath!="")
imwrite(debugPath + "/mask2-3.tif",img_mask*255);
cv::meanStdDev(imageDifference, meanImageDifference, stdDevImageDifference, img_mask);
img_mask.release();
}
else
{
cv::meanStdDev(imageDifference, meanImageDifference, stdDevImageDifference);
}
// Find mean and std dev of background-subtracted image
//threshold for binarization is mean + 3*std_dev
double mean = meanImageDifference.at<double>(0, 0);
double stdev = stdDevImageDifference.at<double>(0, 0);
double threshold_value = mean + (thresholdMultiplier * stdev);
std::cout << "\nmean: " << mean << " std: " << stdev << " thresh: " << threshold_value << "\n";
//get binary (thresholded) image
imageThreshold = MatrixOperations::greaterThanValue((float)threshold_value, imageDifference);
if (debugPath!="")
imwrite(debugPath + "/thresholded2-4.tif",imageThreshold*255);
//std::cout << "thresholded\n";
imageDifference.release(); //FBM
// Only use pixels which pass the threshold from the cross correlation
//I don't understand what this is doing
cv::Mat grayscaleCrossCorrelation = crossCorrelateWithGaussian(image);
cv::bitwise_and(imageThreshold, grayscaleCrossCorrelation, grayscaleImage);
//std::cout << "cross correlated\n";
image.release(); //FBM
imageThreshold.release(); //FBM
grayscaleCrossCorrelation.release(); //FBM
if (debugPath!="")
imwrite(debugPath + "/grayscalecorrelated2-5.tif",grayscaleImage*255);
// Morphological close
cv::Mat closingElement = getStructuringElement(cv::MORPH_RECT, cv::Size(3,3));
cv::morphologyEx(grayscaleImage, grayscaleImage, cv::MORPH_CLOSE, closingElement);
grayscaleImage.convertTo(grayscaleImage, CV_8UC1);
closingElement.release(); //FBM
if (debugPath!="")
imwrite(debugPath + "/grayscaleclsed2-6.tif",grayscaleImage*255);
return grayscaleImage;
}
