c_cpp CV - 检测Harris角落。
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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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