void HereBeDragons::MyNoblerPartToMyGrossBodysTreason(cv::Mat &My){
My = 255 - My;
My /= 255;
cv::Mat prev = cv::Mat::zeros(My.size(), CV_8UC1);
cv::Mat diff;
do {
thinningIteration(My, 0);
thinningIteration(My, 1);
cv::absdiff(My, prev, diff);
My.copyTo(prev);
} while (cv::countNonZero(diff) > 0);
My *= 255;
My = 255 - My;
}
/*
* Function for thinning the given binary image
*
* Based off of code found from here: http://opencv-code.com/quick-tips/implementation-of-thinning-algorithm-in-opencv/
*
* This is part of the Zhang-Suen algorithm, documentation on how it works can be seen here: http://read.pudn.com/downloads99/sourcecode/graph/texture_mapping/403914/Parallel%20thinning%20with%20two- subiteration%20algorithms.pdf
*
* @param im Binary image with range = 0-255
*/
void ImageProcessor::thinning(cv::Mat& im){
im /= 255;
cv::Mat prev = cv::Mat::zeros(im.size(), CV_8UC1);
cv::Mat diff;
do{
thinningIteration(im, 0);
thinningIteration(im, 1);
cv::absdiff(im, prev, diff);
im.copyTo(prev);
} while (cv::countNonZero(diff) > 0);
im *= 255;
}
Mat Thinning::doThinning(Mat img){
// Fast thinning algorithm implmented from https://github.com/bsdnoobz/zhang-suen-thinning
img /= 255;
Mat prev = Mat::zeros(img.size(), CV_8UC1);
Mat diff;
do{
thinningIteration(img, 0);
thinningIteration(img, 1);
absdiff(img, prev, diff);
img.copyTo(prev);
} while (countNonZero(diff) > 0);
img *= 255;
return img;
}
/**
* Function for thinning the given binary image
*
* Parameters:
* src The source image, binary with range = [0,255]
* dst The destination image
*/
void thinningImage(const cv::Mat& src, cv::Mat& dst)
{
dst = src.clone();
dst /= 255; // convert to binary image
cv::Mat prev = cv::Mat::zeros(dst.size(), CV_8UC1);
cv::Mat diff;
do {
thinningIteration(dst, 0);
thinningIteration(dst, 1);
cv::absdiff(dst, prev, diff);
dst.copyTo(prev);
}
while (cv::countNonZero(diff) > 0);
dst *= 255;
}
// Apply the thinning procedure to a given image
void thinning(InputArray input, OutputArray output){
Mat processed = input.getMat().clone();
// Enforce the range of the input image to be in between 0 - 255
processed /= 255;
Mat prev = Mat::zeros(processed.size(), CV_8UC1);
Mat diff;
do {
thinningIteration(processed, 0);
thinningIteration(processed, 1);
absdiff(processed, prev, diff);
processed.copyTo(prev);
}
while (countNonZero(diff) > 0);
processed *= 255;
output.assign(processed);
}
/**
* Function for thinning the given binary image
*
* @param im Binary image with range = 0-255
* @param useGuoHall Use Guo-Hall or Zhang-Suen algorithm
*/
void thinning(cv::Mat& im, bool useGuoHall = false)
{
im /= 255;
if (useGuoHall)
{
cv::Mat diff;
cv::Mat prev = cv::Mat::zeros(im.size(), CV_8UC1);
do {
thinningGuoHallIteration(im, 0);
thinningGuoHallIteration(im, 1);
cv::absdiff(im, prev, diff);
im.copyTo(prev);
} while (cv::countNonZero(diff) > 0);
}
else
{
cv::Mat marker = cv::Mat::ones(im.size(), CV_8UC1);
while (thinningIteration(im, marker) > 0);
}
im *= 255;
}
