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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