mirror of
https://github.com/opencv/opencv.git
synced 2024-12-04 08:49:14 +08:00
242 lines
8.6 KiB
C++
242 lines
8.6 KiB
C++
/*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"
|
|
|
|
#include <limits>
|
|
#include <utility>
|
|
#include <algorithm>
|
|
|
|
#include <math.h>
|
|
|
|
namespace cv {
|
|
|
|
inline bool is_smaller(const std::pair<int, float>& p1, const std::pair<int, float>& p2)
|
|
{
|
|
return p1.second < p2.second;
|
|
}
|
|
|
|
static void orderContours(const std::vector<std::vector<Point> >& contours, Point2f point, std::vector<std::pair<int, float> >& order)
|
|
{
|
|
order.clear();
|
|
size_t i, j, n = contours.size();
|
|
for(i = 0; i < n; i++)
|
|
{
|
|
size_t ni = contours[i].size();
|
|
double min_dist = std::numeric_limits<double>::max();
|
|
for(j = 0; j < ni; j++)
|
|
{
|
|
double dist = norm(Point2f((float)contours[i][j].x, (float)contours[i][j].y) - point);
|
|
min_dist = MIN(min_dist, dist);
|
|
}
|
|
order.push_back(std::pair<int, float>((int)i, (float)min_dist));
|
|
}
|
|
|
|
std::sort(order.begin(), order.end(), is_smaller);
|
|
}
|
|
|
|
// fit second order curve to a set of 2D points
|
|
inline void fitCurve2Order(const std::vector<Point2f>& /*points*/, std::vector<float>& /*curve*/)
|
|
{
|
|
// TBD
|
|
}
|
|
|
|
inline void findCurvesCross(const std::vector<float>& /*curve1*/, const std::vector<float>& /*curve2*/, Point2f& /*cross_point*/)
|
|
{
|
|
}
|
|
|
|
static void findLinesCrossPoint(Point2f origin1, Point2f dir1, Point2f origin2, Point2f dir2, Point2f& cross_point)
|
|
{
|
|
float det = dir2.x*dir1.y - dir2.y*dir1.x;
|
|
Point2f offset = origin2 - origin1;
|
|
|
|
float alpha = (dir2.x*offset.y - dir2.y*offset.x)/det;
|
|
cross_point = origin1 + dir1*alpha;
|
|
}
|
|
|
|
static void findCorner(const std::vector<Point2f>& contour, Point2f point, Point2f& corner)
|
|
{
|
|
// find the nearest point
|
|
double min_dist = std::numeric_limits<double>::max();
|
|
int min_idx = -1;
|
|
|
|
// find corner idx
|
|
for(size_t i = 0; i < contour.size(); i++)
|
|
{
|
|
double dist = norm(contour[i] - point);
|
|
if(dist < min_dist)
|
|
{
|
|
min_dist = dist;
|
|
min_idx = (int)i;
|
|
}
|
|
}
|
|
CV_Assert(min_idx >= 0);
|
|
|
|
// temporary solution, have to make something more precise
|
|
corner = contour[min_idx];
|
|
return;
|
|
}
|
|
|
|
static int segment_hist_max(const Mat& hist, int& low_thresh, int& high_thresh)
|
|
{
|
|
Mat bw;
|
|
double total_sum = sum(hist).val[0];
|
|
|
|
double quantile_sum = 0.0;
|
|
//double min_quantile = 0.2;
|
|
double low_sum = 0;
|
|
double max_segment_length = 0;
|
|
int max_start_x = -1;
|
|
int max_end_x = -1;
|
|
int start_x = 0;
|
|
const double out_of_bells_fraction = 0.1;
|
|
for(int x = 0; x < hist.size[0]; x++)
|
|
{
|
|
quantile_sum += hist.at<float>(x);
|
|
if(quantile_sum < 0.2*total_sum) continue;
|
|
|
|
if(quantile_sum - low_sum > out_of_bells_fraction*total_sum)
|
|
{
|
|
if(max_segment_length < x - start_x)
|
|
{
|
|
max_segment_length = x - start_x;
|
|
max_start_x = start_x;
|
|
max_end_x = x;
|
|
}
|
|
|
|
low_sum = quantile_sum;
|
|
start_x = x;
|
|
}
|
|
}
|
|
|
|
if(start_x == -1)
|
|
{
|
|
return 0;
|
|
}
|
|
else
|
|
{
|
|
low_thresh = cvRound(max_start_x + 0.25*(max_end_x - max_start_x));
|
|
high_thresh = cvRound(max_start_x + 0.75*(max_end_x - max_start_x));
|
|
return 1;
|
|
}
|
|
}
|
|
|
|
}
|
|
|
|
bool cv::find4QuadCornerSubpix(InputArray _img, InputOutputArray _corners, Size region_size)
|
|
{
|
|
CV_INSTRUMENT_REGION()
|
|
|
|
Mat img = _img.getMat(), cornersM = _corners.getMat();
|
|
int ncorners = cornersM.checkVector(2, CV_32F);
|
|
CV_Assert( ncorners >= 0 );
|
|
Point2f* corners = cornersM.ptr<Point2f>();
|
|
const int nbins = 256;
|
|
float ranges[] = {0, 256};
|
|
const float* _ranges = ranges;
|
|
Mat hist;
|
|
|
|
Mat black_comp, white_comp;
|
|
for(int i = 0; i < ncorners; i++)
|
|
{
|
|
int channels = 0;
|
|
Rect roi(cvRound(corners[i].x - region_size.width), cvRound(corners[i].y - region_size.height),
|
|
region_size.width*2 + 1, region_size.height*2 + 1);
|
|
Mat img_roi = img(roi);
|
|
calcHist(&img_roi, 1, &channels, Mat(), hist, 1, &nbins, &_ranges);
|
|
|
|
int black_thresh = 0, white_thresh = 0;
|
|
segment_hist_max(hist, black_thresh, white_thresh);
|
|
|
|
threshold(img, black_comp, black_thresh, 255.0, THRESH_BINARY_INV);
|
|
threshold(img, white_comp, white_thresh, 255.0, THRESH_BINARY);
|
|
|
|
const int erode_count = 1;
|
|
erode(black_comp, black_comp, Mat(), Point(-1, -1), erode_count);
|
|
erode(white_comp, white_comp, Mat(), Point(-1, -1), erode_count);
|
|
|
|
std::vector<std::vector<Point> > white_contours, black_contours;
|
|
std::vector<Vec4i> white_hierarchy, black_hierarchy;
|
|
findContours(black_comp, black_contours, black_hierarchy, RETR_LIST, CHAIN_APPROX_SIMPLE);
|
|
findContours(white_comp, white_contours, white_hierarchy, RETR_LIST, CHAIN_APPROX_SIMPLE);
|
|
|
|
if(black_contours.size() < 5 || white_contours.size() < 5) continue;
|
|
|
|
// find two white and black blobs that are close to the input point
|
|
std::vector<std::pair<int, float> > white_order, black_order;
|
|
orderContours(black_contours, corners[i], black_order);
|
|
orderContours(white_contours, corners[i], white_order);
|
|
|
|
const float max_dist = 10.0f;
|
|
if(black_order[0].second > max_dist || black_order[1].second > max_dist ||
|
|
white_order[0].second > max_dist || white_order[1].second > max_dist)
|
|
{
|
|
continue; // there will be no improvement in this corner position
|
|
}
|
|
|
|
const std::vector<Point>* quads[4] = {&black_contours[black_order[0].first], &black_contours[black_order[1].first],
|
|
&white_contours[white_order[0].first], &white_contours[white_order[1].first]};
|
|
std::vector<Point2f> quads_approx[4];
|
|
Point2f quad_corners[4];
|
|
for(int k = 0; k < 4; k++)
|
|
{
|
|
std::vector<Point2f> temp;
|
|
for(size_t j = 0; j < quads[k]->size(); j++) temp.push_back((*quads[k])[j]);
|
|
approxPolyDP(Mat(temp), quads_approx[k], 0.5, true);
|
|
|
|
findCorner(quads_approx[k], corners[i], quad_corners[k]);
|
|
quad_corners[k] += Point2f(0.5f, 0.5f);
|
|
}
|
|
|
|
// cross two lines
|
|
Point2f origin1 = quad_corners[0];
|
|
Point2f dir1 = quad_corners[1] - quad_corners[0];
|
|
Point2f origin2 = quad_corners[2];
|
|
Point2f dir2 = quad_corners[3] - quad_corners[2];
|
|
double angle = acos(dir1.dot(dir2)/(norm(dir1)*norm(dir2)));
|
|
if(cvIsNaN(angle) || cvIsInf(angle) || angle < 0.5 || angle > CV_PI - 0.5) continue;
|
|
|
|
findLinesCrossPoint(origin1, dir1, origin2, dir2, corners[i]);
|
|
}
|
|
|
|
return true;
|
|
}
|