/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // Intel License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000, Intel Corporation, all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's in binary form must reproduce the above copyright notice, // this list of conditions and the following disclaimer in the documentation // and/or other materials provided with the distribution. // // * The name of Intel Corporation may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #include "precomp.hpp" using namespace std; using namespace cv; /* FeatureDetector */ struct MaskPredicate { MaskPredicate( const Mat& _mask ) : mask(_mask) {} MaskPredicate& operator=(const MaskPredicate&) {} bool operator() (const KeyPoint& key_pt) const { return mask.at( (int)(key_pt.pt.y + 0.5f), (int)(key_pt.pt.x + 0.5f) ) != 0; } const Mat& mask; }; void FeatureDetector::removeInvalidPoints( const Mat& mask, vector& keypoints ) { if( mask.empty() ) return; keypoints.erase(remove_if(keypoints.begin(), keypoints.end(), MaskPredicate(mask)), keypoints.end()); }; /* FastFeatureDetector */ FastFeatureDetector::FastFeatureDetector( int _threshold, bool _nonmaxSuppression ) : threshold(_threshold), nonmaxSuppression(_nonmaxSuppression) {} void FastFeatureDetector::detectImpl( const Mat& image, const Mat& mask, vector& keypoints) const { FAST( image, keypoints, threshold, nonmaxSuppression ); removeInvalidPoints( mask, keypoints ); } /* GoodFeaturesToTrackDetector */ GoodFeaturesToTrackDetector::GoodFeaturesToTrackDetector( int _maxCorners, double _qualityLevel, \ double _minDistance, int _blockSize, bool _useHarrisDetector, double _k ) : maxCorners(_maxCorners), qualityLevel(_qualityLevel), minDistance(_minDistance), blockSize(_blockSize), useHarrisDetector(_useHarrisDetector), k(_k) {} void GoodFeaturesToTrackDetector::detectImpl( const Mat& image, const Mat& mask, vector& keypoints ) const { vector corners; goodFeaturesToTrack( image, corners, maxCorners, qualityLevel, minDistance, mask, blockSize, useHarrisDetector, k ); keypoints.resize(corners.size()); vector::const_iterator corner_it = corners.begin(); vector::iterator keypoint_it = keypoints.begin(); for( ; corner_it != corners.end(); ++corner_it, ++keypoint_it ) { *keypoint_it = KeyPoint( *corner_it, blockSize ); } } /* MserFeatureDetector */ MserFeatureDetector::MserFeatureDetector( int delta, int minArea, int maxArea, float maxVariation, float minDiversity, int maxEvolution, double areaThreshold, double minMargin, int edgeBlurSize ) : mser( delta, minArea, maxArea, maxVariation, minDiversity, maxEvolution, areaThreshold, minMargin, edgeBlurSize ) {} void MserFeatureDetector::detectImpl( const Mat& image, const Mat& mask, vector& keypoints ) const { vector > msers; mser(image, msers, mask); keypoints.resize( msers.size() ); vector >::const_iterator contour_it = msers.begin(); vector::iterator keypoint_it = keypoints.begin(); for( ; contour_it != msers.end(); ++contour_it, ++keypoint_it ) { // TODO check transformation from MSER region to KeyPoint RotatedRect rect = fitEllipse(Mat(*contour_it)); *keypoint_it = KeyPoint( rect.center, sqrt(rect.size.height*rect.size.width), rect.angle); } } /* StarFeatureDetector */ StarFeatureDetector::StarFeatureDetector(int maxSize, int responseThreshold, int lineThresholdProjected, int lineThresholdBinarized, int suppressNonmaxSize) : star( maxSize, responseThreshold, lineThresholdProjected, lineThresholdBinarized, suppressNonmaxSize) {} void StarFeatureDetector::detectImpl( const Mat& image, const Mat& mask, vector& keypoints) const { star(image, keypoints); removeInvalidPoints(mask, keypoints); } /* SiftFeatureDetector */ SiftFeatureDetector::SiftFeatureDetector(double threshold, double edgeThreshold, int nOctaves, int nOctaveLayers, int firstOctave, int angleMode) : sift(threshold, edgeThreshold, nOctaves, nOctaveLayers, firstOctave, angleMode) { } void SiftFeatureDetector::detectImpl( const Mat& image, const Mat& mask, vector& keypoints) const { sift(image, mask, keypoints); } /* SurfFeatureDetector */ SurfFeatureDetector::SurfFeatureDetector( double hessianThreshold, int octaves, int octaveLayers) : surf(hessianThreshold, octaves, octaveLayers) {} void SurfFeatureDetector::detectImpl( const Mat& image, const Mat& mask, vector& keypoints) const { surf(image, mask, keypoints); }