OpenCV定制化创建角点检测子

定制化创建角点检测子

目标

在这个教程中我们将涉及:

使用 OpenCV 函数 cornerEigenValsAndVecs 来计算像素对应的本征值和本征向量来确定其是否是角点。

使用OpenCV 函数 cornerMinEigenVal 通过最小化本征值来进行角点检测。

用上述两个函数实现一个定制化的Harris detector，类似Shi-Tomasi检测子。

解释

代码

这个教程的代码如下所示。源代码还可以从 这个链接下载得到

#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 variables
Mat 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);

char* myHarris_window = "My Harris corner detector";
char* myShiTomasi_window = "My Shi Tomasi corner detector";

/// Function headers
void myShiTomasi_function( int, void* );
void myHarris_function( 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 );

/// 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<float>( j, i, 0 );
float lambda_2 = myHarris_dst.at<float>( j, i, 1 );
Mc.at<float>(j,i) = lambda_1*lambda_2 - 0.04*pow( ( lambda_1 + lambda_2 ), 2 );
}
}

minMaxLoc( Mc, &myHarris_minVal, &myHarris_maxVal, 0, 0, Mat() );

/* Create Window and Trackbar */
namedWindow( myHarris_window, CV_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, CV_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 );
}

解释

结果

翻译者

Shuai Zheng, <kylezheng04@gmail.com>, http://www.cbsr.ia.ac.cn/users/szheng/

from:　http://www.opencv.org.cn/opencvdoc/2.3.2/html/doc/tutorials/features2d/trackingmotion/generic_corner_detector/generic_corner_detector.html#generic-corner-detector