亚像素级的角点检测--goodFeaturesToTrack()

goodFeaturesToTrack()

作用:检测一张图片上的强壮的角点。

形式:void goodFeaturesToTrack(InputArray image, OutputArray corners, int maxCorners, double qualityLevel, double minDistance, InputArray mask=noArray(), int blockSize=3, bool useHarrisDetector=false, double k=0.04 );

参数:

image:输入8位或32位浮点单通道图像;

corners:输出检测角点的向量;

maxCorners:返回角落的最大数量,如果检测到更多的角度,就返回它们中的最强壮的一个;

qualityLevel:表征图像角点的最小可接受质量的参数,参数值乘以最好角点质量--最小特征值或哈里斯函数响应;

minDistance:返回角点之间可能的最小的欧氏距离;

mask:可选的感兴趣区域,如果角点是空的,它就指定了检测到角点的区域;

blockSize:用于计算每个像素领域的协变导数矩阵的平均块大小;

useHarrisDetector:使用哈里斯检测器的指示参数;

k:哈里斯探测器的自由参数;


struct TermCriteria()

作用:设置迭代算法的终止条件;

形式:TermCriteria(int type,int max_iter, double epsilon);

参数:

type:终止条件类型;

CV_TERMCRIT_ITER--max_iter达到最大值后停止算法;

CV_TERMCRIT_EPS--当算法依赖的精确度低于epsilon后,停止算法;

CV_TERMCRIT_ITER+CV_TERMCRIT_EPS--当max_iter达到最大值或算法依赖的精确度低于epsilon任一个满足时,停止算法;

max_iter:最大迭代次数;

epsilon:要求精度;


cornerSubPix()

作用:细化角点位置;

形式:void cornerSubPix(InputArray image, InputOutputArray corners, Size winSize, Size zeroZone, TermCriteria criteria);

参数:

image:输入图像;

corners:初始化输入角点的坐标,为输出提供细化的坐标;

winSize:搜索窗口的边长的一半;

zeroZone:搜索区域中间的死区的一半大小,对它在下边的求和公式不计算,有时候它用来避免可能的自相关矩阵的奇异性,(-1,-1)用来表明这里没有这样的规模;

criteria:角点细化的迭代过程的终止条件;

#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include 
#include 
#include 

using namespace cv;
using namespace std;

/// Global variables
Mat src, src_gray;

int maxCorners = 10;
int maxTrackbar = 25;

RNG rng(12345);
char* source_window = "Image";

/// Function header
void goodFeaturesToTrack_Demo( int, void* );

/** @function main */
int main( int argc, char** argv )
{
  /// Load source image and convert it to gray
  src = imread( argv[1], 1 );
  cvtColor( src, src_gray, CV_BGR2GRAY );

  /// Create Window
  namedWindow( source_window, CV_WINDOW_AUTOSIZE );

  /// Create Trackbar to set the number of corners
  createTrackbar( "Max  corners:", source_window, &maxCorners, maxTrackbar, goodFeaturesToTrack_Demo);

  imshow( source_window, src );

  goodFeaturesToTrack_Demo( 0, 0 );

  waitKey(0);
  return(0);
}

/**
 * @function goodFeaturesToTrack_Demo.cpp
 * @brief Apply Shi-Tomasi corner detector
 */
void goodFeaturesToTrack_Demo( int, void* )
{
  if( maxCorners < 1 ) { maxCorners = 1; }

  /// Parameters for Shi-Tomasi algorithm
  vector corners;
  double qualityLevel = 0.01;
  double minDistance = 10;
  int blockSize = 3;
  bool useHarrisDetector = false;
  double k = 0.04;

  /// Copy the source image
  Mat copy;
  copy = src.clone();

  /// Apply corner detection
  goodFeaturesToTrack( src_gray,
                       corners,
                       maxCorners,
                       qualityLevel,
                       minDistance,
                       Mat(),
                       blockSize,
                       useHarrisDetector,
                       k );


  /// Draw corners detected
  cout<<"** Number of corners detected: "<


你可能感兴趣的:(opencv)