f4334277
 Hu Chunming
提交3rdparty
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/**
* @file KAZE.h
* @brief Main program for detecting and computing descriptors in a nonlinear
* scale space
* @date Jan 21, 2012
* @author Pablo F. Alcantarilla
*/
#ifndef __OPENCV_FEATURES_2D_KAZE_FEATURES_H__
#define __OPENCV_FEATURES_2D_KAZE_FEATURES_H__
/* ************************************************************************* */
// Includes
#include "KAZEConfig.h"
#include "nldiffusion_functions.h"
#include "fed.h"
#include "TEvolution.h"
namespace cv
{
/* ************************************************************************* */
// KAZE Class Declaration
class KAZEFeatures
{
private:
/// Parameters of the Nonlinear diffusion class
KAZEOptions options_; ///< Configuration options for KAZE
std::vector<TEvolution> evolution_; ///< Vector of nonlinear diffusion evolution
/// Vector of keypoint vectors for finding extrema in multiple threads
std::vector<std::vector<cv::KeyPoint> > kpts_par_;
/// FED parameters
int ncycles_; ///< Number of cycles
bool reordering_; ///< Flag for reordering time steps
std::vector<std::vector<float > > tsteps_; ///< Vector of FED dynamic time steps
std::vector<int> nsteps_; ///< Vector of number of steps per cycle
public:
/// Constructor
KAZEFeatures(KAZEOptions& options);
/// Public methods for KAZE interface
void Allocate_Memory_Evolution(void);
int Create_Nonlinear_Scale_Space(const cv::Mat& img);
void Feature_Detection(std::vector<cv::KeyPoint>& kpts);
void Feature_Description(std::vector<cv::KeyPoint>& kpts, cv::Mat& desc);
static void Compute_Main_Orientation(cv::KeyPoint& kpt, const std::vector<TEvolution>& evolution_, const KAZEOptions& options);
/// Feature Detection Methods
void Compute_KContrast(const cv::Mat& img, const float& kper);
void Compute_Multiscale_Derivatives(void);
void Compute_Detector_Response(void);
void Determinant_Hessian(std::vector<cv::KeyPoint>& kpts);
void Do_Subpixel_Refinement(std::vector<cv::KeyPoint>& kpts);
};
}
#endif
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