图像处理——（源）自适应阈值分割（adaptiveThreshold）函数编程实现

 1 #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;    
    cv::blur(src, smooth, cv::Size(Subsize, Subsize));  //均值滤波        
    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("E://lena.jpg");
    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::waitKey(0);
}