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Merge pull request #7516 from sovrasov:find_contours_fix

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pull/7586/head
Alexander Alekhin 8 years ago
parent 51f2b27bcb 56c133d459
commit 4c66772783
4 changed files with 85 additions and 56 deletions
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  1. 3
      modules/calib3d/test/test_chesscorners.cpp
  2. 20
      modules/imgproc/include/opencv2/imgproc.hpp
  3. 82
      modules/imgproc/src/contours.cpp
  4. 20
      modules/imgproc/test/test_contours.cpp

3
modules/calib3d/test/test_chesscorners.cpp
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@ -373,8 +373,6 @@ bool CV_ChessboardDetectorTest::checkByGenerator()
{
bool res = true;
// for some reason, this test sometimes fails on Ubuntu
#if (defined __APPLE__ && defined __x86_64__) || defined _MSC_VER
//theRNG() = 0x58e6e895b9913160;
//cv::DefaultRngAuto dra;
//theRNG() = *ts->get_rng();
@ -473,7 +471,6 @@ bool CV_ChessboardDetectorTest::checkByGenerator()
cv::drawChessboardCorners(cb, cbg.cornersSize(), Mat(corners_found), found);
}
#endif
return res;
}

20
modules/imgproc/include/opencv2/imgproc.hpp
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@ -3732,21 +3732,17 @@ CV_EXPORTS_W int connectedComponentsWithStats(InputArray image, OutputArray labe
/** @brief Finds contours in a binary image.
The function retrieves contours from the binary image using the algorithm @cite Suzuki85 . The contours
are a useful tool for shape analysis and object detection and recognition. See squares.c in the
are a useful tool for shape analysis and object detection and recognition. See squares.cpp in the
OpenCV sample directory.
@note Source image is modified by this function. Also, the function does not take into account
1-pixel border of the image (it's filled with 0's and used for neighbor analysis in the algorithm),
therefore the contours touching the image border will be clipped.
@param image Source, an 8-bit single-channel image. Non-zero pixels are treated as 1's. Zero
pixels remain 0's, so the image is treated as binary . You can use compare , inRange , threshold ,
adaptiveThreshold , Canny , and others to create a binary image out of a grayscale or color one.
The function modifies the image while extracting the contours. If mode equals to RETR_CCOMP
or RETR_FLOODFILL, the input can also be a 32-bit integer image of labels (CV_32SC1).
@param contours Detected contours. Each contour is stored as a vector of points.
@param hierarchy Optional output vector, containing information about the image topology. It has
as many elements as the number of contours. For each i-th contour contours[i] , the elements
pixels remain 0's, so the image is treated as binary . You can use cv::compare, cv::inRange, cv::threshold ,
cv::adaptiveThreshold, cv::Canny, and others to create a binary image out of a grayscale or color one.
If mode equals to cv::RETR_CCOMP or cv::RETR_FLOODFILL, the input can also be a 32-bit integer image of labels (CV_32SC1).
@param contours Detected contours. Each contour is stored as a vector of points (e.g.
std::vector<std::vector<cv::Point> >).
@param hierarchy Optional output vector (e.g. std::vector<cv::Vec4i>), containing information about the image topology. It has
as many elements as the number of contours. For each i-th contour contours[i], the elements
hierarchy[i][0] , hiearchy[i][1] , hiearchy[i][2] , and hiearchy[i][3] are set to 0-based indices
in contours of the next and previous contours at the same hierarchical level, the first child
contour and the parent contour, respectively. If for the contour i there are no next, previous,

82
modules/imgproc/src/contours.cpp
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@ -199,10 +199,10 @@ _CvContourScanner;
Initializes scanner structure.
Prepare image for scanning ( clear borders and convert all pixels to 0-1.
*/
CV_IMPL CvContourScanner
cvStartFindContours( void* _img, CvMemStorage* storage,
static CvContourScanner
cvStartFindContours_Impl( void* _img, CvMemStorage* storage,
int header_size, int mode,
int method, CvPoint offset )
int method, CvPoint offset, int needFillBorder )
{
if( !storage )
CV_Error( CV_StsNullPtr, "" );
@ -310,6 +310,8 @@ cvStartFindContours( void* _img, CvMemStorage* storage,
CV_Assert(size.height >= 1);
/* make zero borders */
if(needFillBorder)
{
int esz = CV_ELEM_SIZE(mat->type);
memset( img, 0, size.width*esz );
memset( img + static_cast<size_t>(step) * (size.height - 1), 0, size.width*esz );
@ -320,6 +322,7 @@ cvStartFindContours( void* _img, CvMemStorage* storage,
for( int k = 0; k < esz; k++ )
img[k] = img[(size.width - 1)*esz + k] = (schar)0;
}
}
/* converts all pixels to 0 or 1 */
if( CV_MAT_TYPE(mat->type) != CV_32S )
@ -328,6 +331,14 @@ cvStartFindContours( void* _img, CvMemStorage* storage,
return scanner;
}
CV_IMPL CvContourScanner
cvStartFindContours( void* _img, CvMemStorage* storage,
int header_size, int mode,
int method, CvPoint offset )
{
return cvStartFindContours_Impl(_img, storage, header_size, mode, method, offset, 1);
}
/*
Final stage of contour processing.
Three variants possible:
@ -1796,33 +1807,11 @@ icvFindContoursInInterval( const CvArr* src,
return count;
}
/*F///////////////////////////////////////////////////////////////////////////////////////
// Name: cvFindContours
// Purpose:
// Finds all the contours on the bi-level image.
// Context:
// Parameters:
// img - source image.
// Non-zero pixels are considered as 1-pixels
// and zero pixels as 0-pixels.
// step - full width of source image in bytes.
// size - width and height of the image in pixels
// storage - pointer to storage where will the output contours be placed.
// header_size - header size of resulting contours
// mode - mode of contour retrieval.
// method - method of approximation that is applied to contours
// first_contour - pointer to first contour pointer
// Returns:
// CV_OK or error code
// Notes:
//F*/
CV_IMPL int
cvFindContours( void* img, CvMemStorage* storage,
static int
cvFindContours_Impl( void* img, CvMemStorage* storage,
CvSeq** firstContour, int cntHeaderSize,
int mode,
int method, CvPoint offset )
int method, CvPoint offset, int needFillBorder )
{
CvContourScanner scanner = 0;
CvSeq *contour = 0;
@ -1845,7 +1834,8 @@ cvFindContours( void* img, CvMemStorage* storage,
{
try
{
scanner = cvStartFindContours( img, storage, cntHeaderSize, mode, method, offset );
scanner = cvStartFindContours_Impl( img, storage, cntHeaderSize, mode, method, offset,
needFillBorder);
do
{
@ -1867,6 +1857,35 @@ cvFindContours( void* img, CvMemStorage* storage,
return count;
}
/*F///////////////////////////////////////////////////////////////////////////////////////
// Name: cvFindContours
// Purpose:
// Finds all the contours on the bi-level image.
// Context:
// Parameters:
// img - source image.
// Non-zero pixels are considered as 1-pixels
// and zero pixels as 0-pixels.
// step - full width of source image in bytes.
// size - width and height of the image in pixels
// storage - pointer to storage where will the output contours be placed.
// header_size - header size of resulting contours
// mode - mode of contour retrieval.
// method - method of approximation that is applied to contours
// first_contour - pointer to first contour pointer
// Returns:
// CV_OK or error code
// Notes:
//F*/
CV_IMPL int
cvFindContours( void* img, CvMemStorage* storage,
CvSeq** firstContour, int cntHeaderSize,
int mode,
int method, CvPoint offset )
{
return cvFindContours_Impl(img, storage, firstContour, cntHeaderSize, mode, method, offset, 1);
}
void cv::findContours( InputOutputArray _image, OutputArrayOfArrays _contours,
OutputArray _hierarchy, int mode, int method, Point offset )
{
@ -1878,13 +1897,14 @@ void cv::findContours( InputOutputArray _image, OutputArrayOfArrays _contours,
CV_Assert(_contours.empty() || (_contours.channels() == 2 && _contours.depth() == CV_32S));
Mat image = _image.getMat();
Mat image;
copyMakeBorder(_image, image, 1, 1, 1, 1, BORDER_CONSTANT, Scalar(0));
MemStorage storage(cvCreateMemStorage());
CvMat _cimage = image;
CvSeq* _ccontours = 0;
if( _hierarchy.needed() )
_hierarchy.clear();
cvFindContours(&_cimage, storage, &_ccontours, sizeof(CvContour), mode, method, offset);
cvFindContours_Impl(&_cimage, storage, &_ccontours, sizeof(CvContour), mode, method, offset + Point(-1, -1), 0);
if( !_ccontours )
{
_contours.clear();

20
modules/imgproc/test/test_contours.cpp
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@ -483,10 +483,26 @@ TEST(Imgproc_FindContours, hilbert)
img.setTo(Scalar::all(0));
drawContours(img, contours, 0, Scalar::all(255), 1);
//imshow("hilbert", img);
//waitKey();
ASSERT_EQ(1, (int)contours.size());
ASSERT_EQ(9832, (int)contours[0].size());
}
TEST(Imgproc_FindContours, border)
{
Mat img;
copyMakeBorder(Mat::zeros(8, 10, CV_8U), img, 1, 1, 1, 1, BORDER_CONSTANT, Scalar(1));
std::vector<std::vector<cv::Point> > contours;
findContours(img, contours, RETR_LIST, CHAIN_APPROX_NONE);
Mat img_draw_contours = Mat::zeros(img.size(), CV_8U);
for (size_t cpt = 0; cpt < contours.size(); cpt++)
{
drawContours(img_draw_contours, contours, static_cast<int>(cpt), cv::Scalar(255));
}
ASSERT_TRUE(norm(img - img_draw_contours, NORM_INF) == 0.0);
}
/* End of file. */

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