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CV - Detect Harris corners.
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/*------------------------------------------------------------------------------------------*\ | |
This file contains material supporting chapter 8 of the cookbook: | |
Computer Vision Programming using the OpenCV Library. | |
by Robert Laganiere, Packt Publishing, 2011. | |
This program is free software; permission is hereby granted to use, copy, modify, | |
and distribute this source code, or portions thereof, for any purpose, without fee, | |
subject to the restriction that the copyright notice may not be removed | |
or altered from any source or altered source distribution. | |
The software is released on an as-is basis and without any warranties of any kind. | |
In particular, the software is not guaranteed to be fault-tolerant or free from failure. | |
The author disclaims all warranties with regard to this software, any use, | |
and any consequent failure, is purely the responsibility of the user. | |
Copyright (C) 2010-2011 Robert Laganiere, www.laganiere.name | |
\*------------------------------------------------------------------------------------------*/ | |
#if !defined HARRISD | |
#define HARRISD | |
#include <vector> | |
#include <opencv2/core/core.hpp> | |
#include <opencv2/imgproc/imgproc.hpp> | |
#include <opencv2/highgui/highgui.hpp> | |
#include <opencv2/features2d/features2d.hpp> | |
class HarrisDetector { | |
private: | |
// 32-bit float image of corner strength | |
cv::Mat cornerStrength; | |
// 32-bit float image of thresholded corners | |
cv::Mat cornerTh; | |
// image of local maxima (internal) | |
cv::Mat localMax; | |
// size of neighbourhood for derivatives smoothing | |
int neighbourhood; | |
// aperture for gradient computation | |
int aperture; | |
// Harris parameter | |
double k; | |
// maximum strength for threshold computation | |
double maxStrength; | |
// calculated threshold (internal) | |
double threshold; | |
// size of neighbourhood for non-max suppression | |
int nonMaxSize; | |
// kernel for non-max suppression | |
cv::Mat kernel; | |
public: | |
HarrisDetector() : neighbourhood(3), aperture(3), k(0.1), maxStrength(0.0), threshold(0.01), nonMaxSize(3) { | |
setLocalMaxWindowSize(nonMaxSize); | |
} | |
// Create kernel used in non-maxima suppression | |
void setLocalMaxWindowSize(int size) { | |
nonMaxSize= size; | |
kernel.create(nonMaxSize,nonMaxSize,CV_8U); | |
} | |
// Compute Harris corners | |
void detect(const cv::Mat& image) { | |
// Harris computation | |
cv::cornerHarris(image,cornerStrength, | |
neighbourhood,// neighborhood size | |
aperture, // aperture size | |
k); // Harris parameter | |
// internal threshold computation | |
double minStrength; // not used | |
cv::minMaxLoc(cornerStrength,&minStrength,&maxStrength); | |
// local maxima detection | |
cv::Mat dilated; // temporary image | |
cv::dilate(cornerStrength,dilated,cv::Mat()); | |
cv::compare(cornerStrength,dilated,localMax,cv::CMP_EQ); | |
} | |
// Get the corner map from the computed Harris values | |
cv::Mat getCornerMap(double qualityLevel) { | |
cv::Mat cornerMap; | |
// thresholding the corner strength | |
threshold= qualityLevel*maxStrength; | |
cv::threshold(cornerStrength,cornerTh,threshold,255,cv::THRESH_BINARY); | |
// convert to 8-bit image | |
cornerTh.convertTo(cornerMap,CV_8U); | |
// non-maxima suppression | |
cv::bitwise_and(cornerMap,localMax,cornerMap); | |
return cornerMap; | |
} | |
// Get the feature points vector from the computed Harris values | |
void getCorners(std::vector<cv::Point> &points, double qualityLevel) { | |
// Get the corner map | |
cv::Mat cornerMap= getCornerMap(qualityLevel); | |
// Get the corners | |
getCorners(points, cornerMap); | |
} | |
// Get the feature points vector from the computed corner map | |
void getCorners(std::vector<cv::Point> &points, const cv::Mat& cornerMap) { | |
// Iterate over the pixels to obtain all feature points | |
for( int y = 0; y < cornerMap.rows; y++ ) { | |
const uchar* rowPtr = cornerMap.ptr<uchar>(y); | |
for( int x = 0; x < cornerMap.cols; x++ ) { | |
// if it is a feature point | |
if (rowPtr[x]) { | |
points.push_back(cv::Point(x,y)); | |
} | |
} | |
} | |
} | |
// Draw circles at feature point locations on an image | |
void drawOnImage(cv::Mat &image, const std::vector<cv::Point> &points, cv::Scalar color= cv::Scalar(255,255,255), int radius=3, int thickness=2) { | |
std::vector<cv::Point>::const_iterator it= points.begin(); | |
// for all corners | |
while (it!=points.end()) { | |
// draw a circle at each corner location | |
cv::circle(image,*it,radius,color,thickness); | |
++it; | |
} | |
} | |
}; | |
#endif |
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