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243 lines
8.2 KiB
C++
243 lines
8.2 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// Intel License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000, Intel Corporation, all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of Intel Corporation may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "precomp.hpp"
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#include <cstdio>
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#include <vector>
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namespace cv
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{
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template<typename T> struct greaterThanPtr
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{
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bool operator()(const T* a, const T* b) const { return *a > *b; }
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};
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}
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void cv::goodFeaturesToTrack( InputArray _image, OutputArray _corners,
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int maxCorners, double qualityLevel, double minDistance,
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InputArray _mask, int blockSize,
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bool useHarrisDetector, double harrisK )
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{
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Mat image = _image.getMat(), mask = _mask.getMat();
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CV_Assert( qualityLevel > 0 && minDistance >= 0 && maxCorners >= 0 );
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CV_Assert( mask.empty() || (mask.type() == CV_8UC1 && mask.size() == image.size()) );
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Mat eig, tmp;
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if( useHarrisDetector )
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cornerHarris( image, eig, blockSize, 3, harrisK );
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else
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cornerMinEigenVal( image, eig, blockSize, 3 );
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double maxVal = 0;
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minMaxLoc( eig, 0, &maxVal, 0, 0, mask );
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threshold( eig, eig, maxVal*qualityLevel, 0, THRESH_TOZERO );
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dilate( eig, tmp, Mat());
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Size imgsize = image.size();
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vector<const float*> tmpCorners;
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// collect list of pointers to features - put them into temporary image
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for( int y = 1; y < imgsize.height - 1; y++ )
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{
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const float* eig_data = (const float*)eig.ptr(y);
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const float* tmp_data = (const float*)tmp.ptr(y);
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const uchar* mask_data = mask.data ? mask.ptr(y) : 0;
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for( int x = 1; x < imgsize.width - 1; x++ )
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{
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float val = eig_data[x];
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if( val != 0 && val == tmp_data[x] && (!mask_data || mask_data[x]) )
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tmpCorners.push_back(eig_data + x);
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}
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}
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sort( tmpCorners, greaterThanPtr<float>() );
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vector<Point2f> corners;
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size_t i, j, total = tmpCorners.size(), ncorners = 0;
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if(minDistance >= 1)
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{
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// Partition the image into larger grids
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int w = image.cols;
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int h = image.rows;
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const int cell_size = cvRound(minDistance);
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const int grid_width = (w + cell_size - 1) / cell_size;
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const int grid_height = (h + cell_size - 1) / cell_size;
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std::vector<std::vector<Point2f> > grid(grid_width*grid_height);
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minDistance *= minDistance;
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for( i = 0; i < total; i++ )
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{
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int ofs = (int)((const uchar*)tmpCorners[i] - eig.data);
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int y = (int)(ofs / eig.step);
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int x = (int)((ofs - y*eig.step)/sizeof(float));
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bool good = true;
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int x_cell = x / cell_size;
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int y_cell = y / cell_size;
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int x1 = x_cell - 1;
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int y1 = y_cell - 1;
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int x2 = x_cell + 1;
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int y2 = y_cell + 1;
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// boundary check
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x1 = std::max(0, x1);
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y1 = std::max(0, y1);
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x2 = std::min(grid_width-1, x2);
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y2 = std::min(grid_height-1, y2);
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for( int yy = y1; yy <= y2; yy++ )
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{
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for( int xx = x1; xx <= x2; xx++ )
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{
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vector <Point2f> &m = grid[yy*grid_width + xx];
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if( m.size() )
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{
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for(j = 0; j < m.size(); j++)
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{
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float dx = x - m[j].x;
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float dy = y - m[j].y;
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if( dx*dx + dy*dy < minDistance )
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{
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good = false;
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goto break_out;
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}
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}
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}
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}
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}
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break_out:
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if(good)
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{
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// printf("%d: %d %d -> %d %d, %d, %d -- %d %d %d %d, %d %d, c=%d\n",
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// i,x, y, x_cell, y_cell, (int)minDistance, cell_size,x1,y1,x2,y2, grid_width,grid_height,c);
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grid[y_cell*grid_width + x_cell].push_back(Point2f((float)x, (float)y));
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corners.push_back(Point2f((float)x, (float)y));
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++ncorners;
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if( maxCorners > 0 && (int)ncorners == maxCorners )
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break;
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}
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}
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}
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else
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{
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for( i = 0; i < total; i++ )
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{
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int ofs = (int)((const uchar*)tmpCorners[i] - eig.data);
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int y = (int)(ofs / eig.step);
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int x = (int)((ofs - y*eig.step)/sizeof(float));
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corners.push_back(Point2f((float)x, (float)y));
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++ncorners;
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if( maxCorners > 0 && (int)ncorners == maxCorners )
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break;
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}
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}
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Mat(corners).convertTo(_corners, _corners.fixedType() ? _corners.type() : CV_32F);
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/*
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for( i = 0; i < total; i++ )
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{
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int ofs = (int)((const uchar*)tmpCorners[i] - eig.data);
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int y = (int)(ofs / eig.step);
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int x = (int)((ofs - y*eig.step)/sizeof(float));
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if( minDistance > 0 )
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{
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for( j = 0; j < ncorners; j++ )
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{
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float dx = x - corners[j].x;
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float dy = y - corners[j].y;
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if( dx*dx + dy*dy < minDistance )
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break;
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}
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if( j < ncorners )
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continue;
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}
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corners.push_back(Point2f((float)x, (float)y));
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++ncorners;
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if( maxCorners > 0 && (int)ncorners == maxCorners )
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break;
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}
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*/
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}
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CV_IMPL void
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cvGoodFeaturesToTrack( const void* _image, void*, void*,
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CvPoint2D32f* _corners, int *_corner_count,
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double quality_level, double min_distance,
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const void* _maskImage, int block_size,
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int use_harris, double harris_k )
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{
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cv::Mat image = cv::cvarrToMat(_image), mask;
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cv::vector<cv::Point2f> corners;
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if( _maskImage )
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mask = cv::cvarrToMat(_maskImage);
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CV_Assert( _corners && _corner_count );
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cv::goodFeaturesToTrack( image, corners, *_corner_count, quality_level,
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min_distance, mask, block_size, use_harris != 0, harris_k );
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size_t i, ncorners = corners.size();
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for( i = 0; i < ncorners; i++ )
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_corners[i] = corners[i];
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*_corner_count = (int)ncorners;
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}
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/* End of file. */
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