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Fix angle discretization in Hough transforms

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In some situations the last value was missing from the discrete theta
values. Now, the last value is chosen such that it is close to the
user-provided maximum theta, while the distance to pi remains always
at least theta_step/2. This should avoid duplicate detections.

A better way would probably be to use max_theta as is and adjust the
resolution (theta_step) instead, such that the discretization would
always be uniform (in a circular sense) when full angle range is used.
This commit is contained in:
lamm45 2022-06-26 19:13:12 -04:00
parent 5e1c9099e8
commit 1f0bfc8d83
3 changed files with 41 additions and 16 deletions
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24
modules/imgproc/include/opencv2/imgproc.hpp
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@ -2024,23 +2024,24 @@ transform.
@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
\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
the image). \f$\theta\f$ is the line rotation angle in radians (
\f$0 \sim \textrm{vertical line}, \pi/2 \sim \textrm{horizontal line}\f$ ).
\f$(\rho, \theta)\f$ or \f$(\rho, \theta, \textrm{votes})\f$, where \f$\rho\f$ is the distance from
the coordinate origin \f$(0,0)\f$ (top-left corner of the image), \f$\theta\f$ is the line rotation
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.
@param rho Distance resolution of the accumulator in pixels.
@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$>\texttt{threshold}\f$ ).
@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
rho/srn . If both srn=0 and stn=0 , the classical Hough transform is used. Otherwise, both these
rho/srn. If both srn=0 and stn=0, the classical Hough transform is used. Otherwise, both these
parameters should be positive.
@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.
Must fall between 0 and max_theta.
@param max_theta For standard and multi-scale Hough transform, maximum angle to check for lines.
Must fall between min_theta and CV_PI.
@param max_theta For standard and multi-scale Hough transform, an upper bound for the angle.
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,
double rho, double theta, int threshold,
@ -2068,7 +2069,7 @@ And this is the output of the above program in case of the probabilistic Hough t
line segment.
@param rho Distance resolution of the accumulator in pixels.
@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$>\texttt{threshold}\f$ ).
@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.
@ -2087,13 +2088,14 @@ 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$(votes, rho, theta)\f$.
The larger the value of 'votes', the higher the reliability of the Hough line.
@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$>\texttt{threshold}\f$ ).
@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 rho_step Distance resolution of the accumulator.
@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.
*/
CV_EXPORTS_W void HoughLinesPointSet( InputArray point, OutputArray lines, int lines_max, int threshold,

22
modules/imgproc/src/hough.cpp
View File

@ -68,6 +68,18 @@ struct hough_cmp_gt
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
createTrigTable( int numangle, double min_theta, double theta_step,
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");
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);
#if defined HAVE_IPP && IPP_VERSION_X100 >= 810 && !IPP_DISABLE_HOUGH
@ -475,7 +487,7 @@ HoughLinesProbabilistic( Mat& image,
int width = image.cols;
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);
#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();
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);
UMat pointsList;
@ -846,7 +858,7 @@ static bool ocl_HoughLinesP(InputArray _src, OutputArray _lines, double rho, dou
}
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);
UMat pointsList;
@ -956,7 +968,7 @@ void HoughLinesPointSet( InputArray _point, OutputArray _lines, int lines_max, i
int i;
float irho = 1 / (float)rho_step;
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);
Mat _accum = Mat::zeros( (numangle+2), (numrho+2), CV_32SC1 );

11
modules/imgproc/test/test_houghlines.cpp
View File

@ -329,6 +329,17 @@ TEST(HoughLinesPointSet, regression_21029)
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" ),
testing::Values( 1, 10 ),
testing::Values( 0.05, 0.1 ),