Merge pull request #22164 from lamm45:hough-angles

Fix angle discretization in Hough transforms
pull/22511/head
Alexander Smorkalov 2 years ago committed by GitHub
commit a72074b33f
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
  1. 20
      modules/imgproc/include/opencv2/imgproc.hpp
  2. 22
      modules/imgproc/src/hough.cpp
  3. 11
      modules/imgproc/test/test_houghlines.cpp

@ -2028,13 +2028,13 @@ transform.
@param image 8-bit, single-channel binary source image. The image may be modified by the function. @param image 8-bit, single-channel binary source image. The image may be modified by the function.
@param lines Output vector of lines. Each line is represented by a 2 or 3 element vector @param lines Output vector of lines. Each line is represented by a 2 or 3 element vector
\f$(\rho, \theta)\f$ or \f$(\rho, \theta, \textrm{votes})\f$ . \f$\rho\f$ is the distance from the coordinate origin \f$(0,0)\f$ (top-left corner of \f$(\rho, \theta)\f$ or \f$(\rho, \theta, \textrm{votes})\f$, where \f$\rho\f$ is the distance from
the image). \f$\theta\f$ is the line rotation angle in radians ( the coordinate origin \f$(0,0)\f$ (top-left corner of the image), \f$\theta\f$ is the line rotation
\f$0 \sim \textrm{vertical line}, \pi/2 \sim \textrm{horizontal line}\f$ ). angle in radians ( \f$0 \sim \textrm{vertical line}, \pi/2 \sim \textrm{horizontal line}\f$ ), and
\f$\textrm{votes}\f$ is the value of accumulator. \f$\textrm{votes}\f$ is the value of accumulator.
@param rho Distance resolution of the accumulator in pixels. @param rho Distance resolution of the accumulator in pixels.
@param theta Angle resolution of the accumulator in radians. @param theta Angle resolution of the accumulator in radians.
@param threshold Accumulator threshold parameter. Only those lines are returned that get enough @param threshold %Accumulator threshold parameter. Only those lines are returned that get enough
votes ( \f$>\texttt{threshold}\f$ ). votes ( \f$>\texttt{threshold}\f$ ).
@param srn For the multi-scale Hough transform, it is a divisor for the distance resolution rho. @param srn For the multi-scale Hough transform, it is a divisor for the distance resolution rho.
The coarse accumulator distance resolution is rho and the accurate accumulator resolution is The coarse accumulator distance resolution is rho and the accurate accumulator resolution is
@ -2043,8 +2043,9 @@ parameters should be positive.
@param stn For the multi-scale Hough transform, it is a divisor for the distance resolution theta. @param stn For the multi-scale Hough transform, it is a divisor for the distance resolution theta.
@param min_theta For standard and multi-scale Hough transform, minimum angle to check for lines. @param min_theta For standard and multi-scale Hough transform, minimum angle to check for lines.
Must fall between 0 and max_theta. Must fall between 0 and max_theta.
@param max_theta For standard and multi-scale Hough transform, maximum angle to check for lines. @param max_theta For standard and multi-scale Hough transform, an upper bound for the angle.
Must fall between min_theta and CV_PI. Must fall between min_theta and CV_PI. The actual maximum angle in the accumulator may be slightly
less than max_theta, depending on the parameters min_theta and theta.
*/ */
CV_EXPORTS_W void HoughLines( InputArray image, OutputArray lines, CV_EXPORTS_W void HoughLines( InputArray image, OutputArray lines,
double rho, double theta, int threshold, double rho, double theta, int threshold,
@ -2072,7 +2073,7 @@ And this is the output of the above program in case of the probabilistic Hough t
line segment. line segment.
@param rho Distance resolution of the accumulator in pixels. @param rho Distance resolution of the accumulator in pixels.
@param theta Angle resolution of the accumulator in radians. @param theta Angle resolution of the accumulator in radians.
@param threshold Accumulator threshold parameter. Only those lines are returned that get enough @param threshold %Accumulator threshold parameter. Only those lines are returned that get enough
votes ( \f$>\texttt{threshold}\f$ ). votes ( \f$>\texttt{threshold}\f$ ).
@param minLineLength Minimum line length. Line segments shorter than that are rejected. @param minLineLength Minimum line length. Line segments shorter than that are rejected.
@param maxLineGap Maximum allowed gap between points on the same line to link them. @param maxLineGap Maximum allowed gap between points on the same line to link them.
@ -2091,13 +2092,14 @@ The function finds lines in a set of points using a modification of the Hough tr
@param lines Output vector of found lines. Each vector is encoded as a vector<Vec3d> \f$(votes, rho, theta)\f$. @param lines Output vector of found lines. Each vector is encoded as a vector<Vec3d> \f$(votes, rho, theta)\f$.
The larger the value of 'votes', the higher the reliability of the Hough line. The larger the value of 'votes', the higher the reliability of the Hough line.
@param lines_max Max count of Hough lines. @param lines_max Max count of Hough lines.
@param threshold Accumulator threshold parameter. Only those lines are returned that get enough @param threshold %Accumulator threshold parameter. Only those lines are returned that get enough
votes ( \f$>\texttt{threshold}\f$ ). votes ( \f$>\texttt{threshold}\f$ ).
@param min_rho Minimum value for \f$\rho\f$ for the accumulator (Note: \f$\rho\f$ can be negative. The absolute value \f$|\rho|\f$ is the distance of a line to the origin.). @param min_rho Minimum value for \f$\rho\f$ for the accumulator (Note: \f$\rho\f$ can be negative. The absolute value \f$|\rho|\f$ is the distance of a line to the origin.).
@param max_rho Maximum value for \f$\rho\f$ for the accumulator. @param max_rho Maximum value for \f$\rho\f$ for the accumulator.
@param rho_step Distance resolution of the accumulator. @param rho_step Distance resolution of the accumulator.
@param min_theta Minimum angle value of the accumulator in radians. @param min_theta Minimum angle value of the accumulator in radians.
@param max_theta Maximum angle value of the accumulator in radians. @param max_theta Upper bound for the angle value of the accumulator in radians. The actual maximum
angle may be slightly less than max_theta, depending on the parameters min_theta and theta_step.
@param theta_step Angle resolution of the accumulator in radians. @param theta_step Angle resolution of the accumulator in radians.
*/ */
CV_EXPORTS_W void HoughLinesPointSet( InputArray point, OutputArray lines, int lines_max, int threshold, CV_EXPORTS_W void HoughLinesPointSet( InputArray point, OutputArray lines, int lines_max, int threshold,

@ -68,6 +68,18 @@ struct hough_cmp_gt
const int* aux; const int* aux;
}; };
static inline int
computeNumangle( double min_theta, double max_theta, double theta_step )
{
int numangle = cvFloor((max_theta - min_theta) / theta_step) + 1;
// If the distance between the first angle and the last angle is
// approximately equal to pi, then the last angle will be removed
// in order to prevent a line to be detected twice.
if ( numangle > 1 && fabs(CV_PI - (numangle-1)*theta_step) < theta_step/2 )
--numangle;
return numangle;
}
static void static void
createTrigTable( int numangle, double min_theta, double theta_step, createTrigTable( int numangle, double min_theta, double theta_step,
float irho, float *tabSin, float *tabCos ) float irho, float *tabSin, float *tabCos )
@ -130,7 +142,7 @@ HoughLinesStandard( InputArray src, OutputArray lines, int type,
CV_CheckGE(max_theta, min_theta, "max_theta must be greater than min_theta"); CV_CheckGE(max_theta, min_theta, "max_theta must be greater than min_theta");
int numangle = cvRound((max_theta - min_theta) / theta); int numangle = computeNumangle(min_theta, max_theta, theta);
int numrho = cvRound(((max_rho - min_rho) + 1) / rho); int numrho = cvRound(((max_rho - min_rho) + 1) / rho);
#if defined HAVE_IPP && IPP_VERSION_X100 >= 810 && !IPP_DISABLE_HOUGH #if defined HAVE_IPP && IPP_VERSION_X100 >= 810 && !IPP_DISABLE_HOUGH
@ -475,7 +487,7 @@ HoughLinesProbabilistic( Mat& image,
int width = image.cols; int width = image.cols;
int height = image.rows; int height = image.rows;
int numangle = cvRound(CV_PI / theta); int numangle = computeNumangle(0.0, CV_PI, theta);
int numrho = cvRound(((width + height) * 2 + 1) / rho); int numrho = cvRound(((width + height) * 2 + 1) / rho);
#if defined HAVE_IPP && IPP_VERSION_X100 >= 810 && !IPP_DISABLE_HOUGH #if defined HAVE_IPP && IPP_VERSION_X100 >= 810 && !IPP_DISABLE_HOUGH
@ -792,7 +804,7 @@ static bool ocl_HoughLines(InputArray _src, OutputArray _lines, double rho, doub
} }
UMat src = _src.getUMat(); UMat src = _src.getUMat();
int numangle = cvRound((max_theta - min_theta) / theta); int numangle = computeNumangle(min_theta, max_theta, theta);
int numrho = cvRound(((src.cols + src.rows) * 2 + 1) / rho); int numrho = cvRound(((src.cols + src.rows) * 2 + 1) / rho);
UMat pointsList; UMat pointsList;
@ -846,7 +858,7 @@ static bool ocl_HoughLinesP(InputArray _src, OutputArray _lines, double rho, dou
} }
UMat src = _src.getUMat(); UMat src = _src.getUMat();
int numangle = cvRound(CV_PI / theta); int numangle = computeNumangle(0.0, CV_PI, theta);
int numrho = cvRound(((src.cols + src.rows) * 2 + 1) / rho); int numrho = cvRound(((src.cols + src.rows) * 2 + 1) / rho);
UMat pointsList; UMat pointsList;
@ -956,7 +968,7 @@ void HoughLinesPointSet( InputArray _point, OutputArray _lines, int lines_max, i
int i; int i;
float irho = 1 / (float)rho_step; float irho = 1 / (float)rho_step;
float irho_min = ((float)min_rho * irho); float irho_min = ((float)min_rho * irho);
int numangle = cvRound((max_theta - min_theta) / theta_step); int numangle = computeNumangle(min_theta, max_theta, theta_step);
int numrho = cvRound((max_rho - min_rho + 1) / rho_step); int numrho = cvRound((max_rho - min_rho + 1) / rho_step);
Mat _accum = Mat::zeros( (numangle+2), (numrho+2), CV_32SC1 ); Mat _accum = Mat::zeros( (numangle+2), (numrho+2), CV_32SC1 );

@ -329,6 +329,17 @@ TEST(HoughLinesPointSet, regression_21029)
EXPECT_TRUE(lines.empty()); EXPECT_TRUE(lines.empty());
} }
TEST(HoughLines, regression_21983)
{
Mat img(200, 200, CV_8UC1, Scalar(0));
line(img, Point(0, 100), Point(100, 100), Scalar(255));
std::vector<Vec2f> lines;
HoughLines(img, lines, 1, CV_PI/180, 90, 0, 0, 0.001, 1.58);
ASSERT_EQ(lines.size(), 1U);
EXPECT_EQ(lines[0][0], 100);
EXPECT_NEAR(lines[0][1], 1.57179642, 1e-4);
}
INSTANTIATE_TEST_CASE_P( ImgProc, StandartHoughLinesTest, testing::Combine(testing::Values( "shared/pic5.png", "../stitching/a1.png" ), INSTANTIATE_TEST_CASE_P( ImgProc, StandartHoughLinesTest, testing::Combine(testing::Values( "shared/pic5.png", "../stitching/a1.png" ),
testing::Values( 1, 10 ), testing::Values( 1, 10 ),
testing::Values( 0.05, 0.1 ), testing::Values( 0.05, 0.1 ),

Loading…
Cancel
Save