Open Source Computer Vision Library https://opencv.org/
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/*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.
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// * 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
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// 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
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//
//M*/
#include "precomp.hpp"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/calib3d/calib3d_c.h"
#include <vector>
#include <algorithm>
//#define DEBUG_WINDOWS
#if defined(DEBUG_WINDOWS)
# include "opencv2/opencv_modules.hpp"
# ifdef HAVE_OPENCV_HIGHGUI
# include "opencv2/highgui.hpp"
# else
# undef DEBUG_WINDOWS
# endif
#endif
static void icvGetQuadrangleHypotheses(CvSeq* contours, std::vector<std::pair<float, int> >& quads, int class_id)
{
const float min_aspect_ratio = 0.3f;
const float max_aspect_ratio = 3.0f;
const float min_box_size = 10.0f;
for(CvSeq* seq = contours; seq != NULL; seq = seq->h_next)
{
CvBox2D box = cvMinAreaRect2(seq);
float box_size = MAX(box.size.width, box.size.height);
if(box_size < min_box_size)
{
continue;
}
float aspect_ratio = box.size.width/MAX(box.size.height, 1);
if(aspect_ratio < min_aspect_ratio || aspect_ratio > max_aspect_ratio)
{
continue;
}
quads.push_back(std::pair<float, int>(box_size, class_id));
}
}
static void countClasses(const std::vector<std::pair<float, int> >& pairs, size_t idx1, size_t idx2, std::vector<int>& counts)
{
counts.assign(2, 0);
for(size_t i = idx1; i != idx2; i++)
{
counts[pairs[i].second]++;
}
}
inline bool less_pred(const std::pair<float, int>& p1, const std::pair<float, int>& p2)
{
return p1.first < p2.first;
}
// does a fast check if a chessboard is in the input image. This is a workaround to
// a problem of cvFindChessboardCorners being slow on images with no chessboard
// - src: input image
// - size: chessboard size
// Returns 1 if a chessboard can be in this image and findChessboardCorners should be called,
// 0 if there is no chessboard, -1 in case of error
int cvCheckChessboard(IplImage* src, CvSize size)
{
if(src->nChannels > 1)
{
cvError(CV_BadNumChannels, "cvCheckChessboard", "supports single-channel images only",
__FILE__, __LINE__);
}
if(src->depth != 8)
{
cvError(CV_BadDepth, "cvCheckChessboard", "supports depth=8 images only",
__FILE__, __LINE__);
}
const int erosion_count = 1;
const float black_level = 20.f;
const float white_level = 130.f;
const float black_white_gap = 70.f;
#if defined(DEBUG_WINDOWS)
cvNamedWindow("1", 1);
cvShowImage("1", src);
cvWaitKey(0);
#endif //DEBUG_WINDOWS
CvMemStorage* storage = cvCreateMemStorage();
IplImage* white = cvCloneImage(src);
IplImage* black = cvCloneImage(src);
cvErode(white, white, NULL, erosion_count);
cvDilate(black, black, NULL, erosion_count);
IplImage* thresh = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1);
int result = 0;
for(float thresh_level = black_level; thresh_level < white_level && !result; thresh_level += 20.0f)
{
cvThreshold(white, thresh, thresh_level + black_white_gap, 255, CV_THRESH_BINARY);
#if defined(DEBUG_WINDOWS)
cvShowImage("1", thresh);
cvWaitKey(0);
#endif //DEBUG_WINDOWS
CvSeq* first = 0;
std::vector<std::pair<float, int> > quads;
cvFindContours(thresh, storage, &first, sizeof(CvContour), CV_RETR_CCOMP);
icvGetQuadrangleHypotheses(first, quads, 1);
cvThreshold(black, thresh, thresh_level, 255, CV_THRESH_BINARY_INV);
#if defined(DEBUG_WINDOWS)
cvShowImage("1", thresh);
cvWaitKey(0);
#endif //DEBUG_WINDOWS
cvFindContours(thresh, storage, &first, sizeof(CvContour), CV_RETR_CCOMP);
icvGetQuadrangleHypotheses(first, quads, 0);
const size_t min_quads_count = size.width*size.height/2;
std::sort(quads.begin(), quads.end(), less_pred);
// now check if there are many hypotheses with similar sizes
// do this by floodfill-style algorithm
const float size_rel_dev = 0.4f;
for(size_t i = 0; i < quads.size(); i++)
{
size_t j = i + 1;
for(; j < quads.size(); j++)
{
if(quads[j].first/quads[i].first > 1.0f + size_rel_dev)
{
break;
}
}
if(j + 1 > min_quads_count + i)
{
// check the number of black and white squares
std::vector<int> counts;
countClasses(quads, i, j, counts);
const int black_count = cvRound(ceil(size.width/2.0)*ceil(size.height/2.0));
const int white_count = cvRound(floor(size.width/2.0)*floor(size.height/2.0));
if(counts[0] < black_count*0.75 ||
counts[1] < white_count*0.75)
{
continue;
}
result = 1;
break;
}
}
}
cvReleaseImage(&thresh);
cvReleaseImage(&white);
cvReleaseImage(&black);
cvReleaseMemStorage(&storage);
return result;
}