#include <iostream>
#include <opencv2/core.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/imgproc.hpp>
enum adaptiveMethod{meanFilter,gaaussianFilter,medianFilter};
void AdaptiveThreshold(cv::Mat& src, cv::Mat& dst, double Maxval, int Subsize, double c, adaptiveMethod method = meanFilter){
if (src.channels() > 1)
cv::cvtColor(src, src, CV_RGB2GRAY);
cv::Mat smooth;
switch (method)
{
case meanFilter:
cv::blur(src, smooth, cv::Size(Subsize, Subsize));
break;
case gaaussianFilter:
cv::GaussianBlur(src, smooth, cv::Size(Subsize, Subsize),0,0);
break;
case medianFilter:
cv::medianBlur(src, smooth, Subsize);
break;
default:
break;
}
smooth = smooth - c;
//阈值处理
src.copyTo(dst);
for (int r = 0; r < src.rows;++r){
const uchar* srcptr = src.ptr<uchar>(r);
const uchar* smoothptr = smooth.ptr<uchar>(r);
uchar* dstptr = dst.ptr<uchar>(r);
for (int c = 0; c < src.cols; ++c){
if (srcptr[c]>smoothptr[c]){
dstptr[c] = Maxval;
}
else
dstptr[c] = 0;
}
}
}
int main(){
cv::Mat src = cv::imread("I:\\Learning-and-Practice\\2019Change\\Image process algorithm\\Img\\Fig1049(a)(spot_shaded_text_image).tif");
if (src.empty()){
return -1;
}
if (src.channels() > 1)
cv::cvtColor(src, src, CV_RGB2GRAY);
cv::Mat dst, dst2;
double t2 = (double)cv::getTickCount();
AdaptiveThreshold(src, dst, 255, 21, 10, meanFilter); //
t2 = (double)cv::getTickCount() - t2;
double time2 = (t2 *1000.) / ((double)cv::getTickFrequency());
std::cout << "my_process=" << time2 << " ms. " << std::endl << std::endl;
cv::adaptiveThreshold(src, dst2, 255, cv::ADAPTIVE_THRESH_MEAN_C, cv::THRESH_BINARY, 21, 10);
cv::namedWindow("src", CV_WINDOW_NORMAL);
cv::imshow("src", src);
cv::namedWindow("dst", CV_WINDOW_NORMAL);
cv::imshow("dst", dst);
cv::namedWindow("dst2", CV_WINDOW_NORMAL);
cv::imshow("dst2", dst2);
//cv::imwrite("I:\\Learning-and-Practice\\2019Change\\Image process algorithm\\Image Filtering\\MeanFilter\\TXT.jpg",dst);
cv::waitKey(0);
}
