首页 > 代码库 > OpenCV Tutorials —— Creating yor own corner detector

OpenCV Tutorials —— Creating yor own corner detector

2024-08-04 14:52:15   223人阅读

  • Use the OpenCV function cornerEigenValsAndVecs to find the eigenvalues and eigenvectors to determine if a pixel is a corner.
  • Use the OpenCV function cornerMinEigenVal to find the minimum eigenvalues for corner detection.

 

最小特征值对应的角点监测 ~~

对自相关矩阵 M 进行特征值分析，产生两个特征值和两个特征方向向量。因为较大的不确定度取决于较小的特征值，也就是，所以通过寻找最小特征值的最大值来寻找好的特征点

 

void cornerEigenValsAndVecs(InputArray src, OutputArray dst, int blockSize, int ksize, intborderType=BORDER_DEFAULT )

Parameters:

  • src – Input single-channel 8-bit or floating-point image.
  • dst – Image to store the results. It has the same size as src and the type CV_32FC(6) .
  • blockSize – Neighborhood size (see details below).
  • ksize – Aperture parameter for the Sobel() operator.
  • borderType – Pixel extrapolation method. See borderInterpolate() .

 

For every pixel p , the function cornerEigenValsAndVecs considers a blockSize \times blockSize neighborhood S(p) . It calculates the covariation matrix of derivatives over the neighborhood as:  导数的共生矩阵 ~~ 导数的自相关矩阵

M = \begin{bmatrix} \sum _{S(p)}(dI/dx)^2 & \sum _{S(p)}(dI/dx dI/dy)^2 \\ \sum _{S(p)}(dI/dx dI/dy)^2 & \sum _{S(p)}(dI/dy)^2 \end{bmatrix}

 

void cornerMinEigenVal(InputArray src, OutputArray dst, int blockSize, int ksize=3, intborderType=BORDER_DEFAULT )

Parameters:

  • src – Input single-channel 8-bit or floating-point image.
  • dst – Image to store the minimal eigenvalues. It has the type CV_32FC1 and the same size as src .
  • blockSize – Neighborhood size (see the details on cornerEigenValsAndVecs() ).
  • ksize – Aperture parameter for the Sobel() operator.
  • borderType – Pixel extrapolation method. See borderInterpolate() .

 

The function is similar to cornerEigenValsAndVecs() but it calculates and stores only the minimal eigenvalue of the covariance matrix of derivatives

 

Code

#include "stdafx.h"#include "opencv2/highgui/highgui.hpp"#include "opencv2/imgproc/imgproc.hpp"#include <iostream>#include <stdio.h>#include <stdlib.h>using namespace cv;using namespace std;/// Global variablesMat src, src_gray;Mat myHarris_dst; Mat myHarris_copy; Mat Mc;Mat myShiTomasi_dst; Mat myShiTomasi_copy;int myShiTomasi_qualityLevel = 50;int myHarris_qualityLevel = 50;int max_qualityLevel = 100;double myHarris_minVal; double myHarris_maxVal;double myShiTomasi_minVal; double myShiTomasi_maxVal;RNG rng(12345);const char* myHarris_window = "My Harris corner detector";const char* myShiTomasi_window = "My Shi Tomasi corner detector";/// Function headersvoid myShiTomasi_function( int, void* );void myHarris_function( int, void* );/** * @function main */int main( int, char** argv ){  /// Load source image and convert it to gray  src = http://www.mamicode.com/imread("xue.jpg", 1 );  cvtColor( src, src_gray, COLOR_BGR2GRAY );  /// Set some parameters  int blockSize = 3; int apertureSize = 3;  /// My Harris matrix -- Using cornerEigenValsAndVecs  myHarris_dst = Mat::zeros( src_gray.size(), CV_32FC(6) );  Mc = Mat::zeros( src_gray.size(), CV_32FC1 );  cornerEigenValsAndVecs( src_gray, myHarris_dst, blockSize, apertureSize, BORDER_DEFAULT );  /* calculate Mc */  for( int j = 0; j < src_gray.rows; j++ )     { for( int i = 0; i < src_gray.cols; i++ )          {            float lambda_1 = myHarris_dst.at<Vec6f>(j, i)[0];            float lambda_2 = myHarris_dst.at<Vec6f>(j, i)[1];            Mc.at<float>(j,i) = lambda_1*lambda_2 - 0.04f*pow( ( lambda_1 + lambda_2 ), 2 );          }     }  minMaxLoc( Mc, &myHarris_minVal, &myHarris_maxVal, 0, 0, Mat() );  /* Create Window and Trackbar */  namedWindow( myHarris_window, WINDOW_AUTOSIZE );  createTrackbar( " Quality Level:", myHarris_window, &myHarris_qualityLevel, max_qualityLevel, myHarris_function );  myHarris_function( 0, 0 );  /// My Shi-Tomasi -- Using cornerMinEigenVal  myShiTomasi_dst = Mat::zeros( src_gray.size(), CV_32FC1 );  cornerMinEigenVal( src_gray, myShiTomasi_dst, blockSize, apertureSize, BORDER_DEFAULT );  minMaxLoc( myShiTomasi_dst, &myShiTomasi_minVal, &myShiTomasi_maxVal, 0, 0, Mat() );  /* Create Window and Trackbar */  namedWindow( myShiTomasi_window, WINDOW_AUTOSIZE );  createTrackbar( " Quality Level:", myShiTomasi_window, &myShiTomasi_qualityLevel, max_qualityLevel, myShiTomasi_function );  myShiTomasi_function( 0, 0 );  waitKey(0);  return(0);}/** * @function myShiTomasi_function */void myShiTomasi_function( int, void* ){  myShiTomasi_copy = src.clone();  if( myShiTomasi_qualityLevel < 1 ) { myShiTomasi_qualityLevel = 1; }  for( int j = 0; j < src_gray.rows; j++ )     { for( int i = 0; i < src_gray.cols; i++ )          {            if( myShiTomasi_dst.at<float>(j,i) > myShiTomasi_minVal + ( myShiTomasi_maxVal - myShiTomasi_minVal )*myShiTomasi_qualityLevel/max_qualityLevel )              { circle( myShiTomasi_copy, Point(i,j), 4, Scalar( rng.uniform(0,255), rng.uniform(0,255), rng.uniform(0,255) ), -1, 8, 0 ); }          }     }  imshow( myShiTomasi_window, myShiTomasi_copy );}/** * @function myHarris_function */void myHarris_function( int, void* ){  myHarris_copy = src.clone();  if( myHarris_qualityLevel < 1 ) { myHarris_qualityLevel = 1; }  for( int j = 0; j < src_gray.rows; j++ )     { for( int i = 0; i < src_gray.cols; i++ )          {            if( Mc.at<float>(j,i) > myHarris_minVal + ( myHarris_maxVal - myHarris_minVal )*myHarris_qualityLevel/max_qualityLevel )              { circle( myHarris_copy, Point(i,j), 4, Scalar( rng.uniform(0,255), rng.uniform(0,255), rng.uniform(0,255) ), -1, 8, 0 ); }          }     }  imshow( myHarris_window, myHarris_copy );}

OpenCV Tutorials —— Creating yor own corner detector


联系
我们