C(OPENCV)中精确的亚像素边缘定位

时间:2016-03-01 21:06:29

标签: opencv subpixel

我想找到subpixel并且我研究了这个主题但是我认为子像素必须是如152.6,49.3 ...... 我在opencv http://docs.opencv.org/2.4/modules/imgproc/doc/feature_detection.html?highlight=cornersubpix#cornersubpix中找到了这个文档  我试试这段代码

    #include <iostream>
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
#include <stdlib.h>

using namespace cv;
using namespace std;

Mat src, src_gray;
int maxCorners = 10;
int maxTrackbar = 50;
RNG rng(11111);
char* source_window = "Image";
void goodFeaturesToTrack_Demo( int, void* );
int main( int argc, char** argv )
{
  src = imread( "a.png", 1 );
  cvtColor( src, src_gray, CV_BGR2GRAY );
  namedWindow( source_window, CV_WINDOW_AUTOSIZE );
  createTrackbar( "Max  corners:", source_window, &maxCorners, maxTrackbar, goodFeaturesToTrack_Demo);
  imshow( source_window, src );
  goodFeaturesToTrack_Demo( 0, 0 );
  waitKey(0);
  return(0);
}
void goodFeaturesToTrack_Demo( int, void* )
{
  if( maxCorners < 1 ) 
  { maxCorners = 1; }
  vector<Point2f> corners;
  double qualityLevel = 0.01;
  double minDistance = 10;
  int blockSize = 3;
  bool useHarrisDetector = false;
  double k = 0.04;
  Mat copy;
  copy = src.clone();
  goodFeaturesToTrack( src_gray,corners,maxCorners,qualityLevel,minDistance,Mat(),blockSize,useHarrisDetector,k );
  cout<<"** Number of corners detected: "<<corners.size()<<endl;
  int r = 4;
  for( int i = 0; i < corners.size(); i++ )
     { circle( copy, corners[i], r, Scalar(rng.uniform(0,255), rng.uniform(0,255),rng.uniform(0,255)), -1, 8, 0 ); }
  namedWindow( source_window, CV_WINDOW_AUTOSIZE );
  imshow( source_window, copy );
  Size winSize = Size( 10, 10 );
  Size zeroZone = Size( -1, -1 );
  TermCriteria criteria = TermCriteria( CV_TERMCRIT_EPS + CV_TERMCRIT_ITER, 40, 0.001 );
  cornerSubPix( src_gray, corners, winSize, zeroZone, criteria );
  for( int i = 0; i < corners.size(); i++ )
     { cout<<" -- Refined Corner ["<<i<<"]  ("<<corners[i].x<<","<<corners[i].y<<")"<<endl; }
}

但我有这个结果:

此代码仅限角落的子像素我想找到边缘的子像素

0 个答案:

没有答案