Package org.opencv.imgproc

Class LineSegmentDetector

java.lang.Object

org.opencv.core.Algorithm

org.opencv.imgproc.LineSegmentDetector

public class LineSegmentDetector
extends Algorithm

Line segment detector class following the algorithm described at CITE: Rafael12 . Note: Implementation has been removed due original code license conflict

Field Summary

Fields inherited from class org.opencv.core.Algorithm

nativeObj

Constructor Summary

Constructors

Modifier	Constructor	Description
protected	LineSegmentDetector(long addr)

Method Summary

Modifier and Type	Method	Description
static LineSegmentDetector	__fromPtr__(long addr)
int	compareSegments(Size size, Mat lines1, Mat lines2)	Draws two groups of lines in blue and red, counting the non overlapping (mismatching) pixels.
int	compareSegments(Size size, Mat lines1, Mat lines2, Mat _image)	Draws two groups of lines in blue and red, counting the non overlapping (mismatching) pixels.
void	detect(Mat _image, Mat _lines)	Finds lines in the input image.
void	detect(Mat _image, Mat _lines, Mat width)	Finds lines in the input image.
void	detect(Mat _image, Mat _lines, Mat width, Mat prec)	Finds lines in the input image.
void	detect(Mat _image, Mat _lines, Mat width, Mat prec, Mat nfa)	Finds lines in the input image.
void	drawSegments(Mat _image, Mat lines)	Draws the line segments on a given image.
protected void	finalize()

Methods inherited from class org.opencv.core.Algorithm

clear, empty, getDefaultName, getNativeObjAddr, save

Methods inherited from class java.lang.Object

clone, equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

LineSegmentDetector

protected LineSegmentDetector(long addr)

Method Detail

__fromPtr__

public static LineSegmentDetector __fromPtr__(long addr)

compareSegments

public int compareSegments(Size size,
                           Mat lines1,
                           Mat lines2,
                           Mat _image)

Draws two groups of lines in blue and red, counting the non overlapping (mismatching) pixels.

Parameters:

size - The size of the image, where lines1 and lines2 were found.

lines1 - The first group of lines that needs to be drawn. It is visualized in blue color.

lines2 - The second group of lines. They visualized in red color.

_image - Optional image, where the lines will be drawn. The image should be color(3-channel) in order for lines1 and lines2 to be drawn in the above mentioned colors.

Returns:

automatically generated

compareSegments

public int compareSegments(Size size,
                           Mat lines1,
                           Mat lines2)

Draws two groups of lines in blue and red, counting the non overlapping (mismatching) pixels.

Parameters:

size - The size of the image, where lines1 and lines2 were found.

lines1 - The first group of lines that needs to be drawn. It is visualized in blue color.

lines2 - The second group of lines. They visualized in red color. in order for lines1 and lines2 to be drawn in the above mentioned colors.

Returns:

automatically generated

detect

public void detect(Mat _image,
                   Mat _lines,
                   Mat width,
                   Mat prec,
                   Mat nfa)

Finds lines in the input image. This is the output of the default parameters of the algorithm on the above shown image. 

Parameters:

_image - A grayscale (CV_8UC1) input image. If only a roi needs to be selected, use: lsd_ptr->detect(image(roi), lines, ...); lines += Scalar(roi.x, roi.y, roi.x, roi.y);

_lines - A vector of Vec4i or Vec4f elements specifying the beginning and ending point of a line. Where Vec4i/Vec4f is (x1, y1, x2, y2), point 1 is the start, point 2 - end. Returned lines are strictly oriented depending on the gradient.

width - Vector of widths of the regions, where the lines are found. E.g. Width of line.

prec - Vector of precisions with which the lines are found.

nfa - Vector containing number of false alarms in the line region, with precision of 10%. The bigger the value, logarithmically better the detection.

• -1 corresponds to 10 mean false alarms
• 0 corresponds to 1 mean false alarm
• 1 corresponds to 0.1 mean false alarms This vector will be calculated only when the objects type is #LSD_REFINE_ADV.

detect

public void detect(Mat _image,
                   Mat _lines,
                   Mat width,
                   Mat prec)

Finds lines in the input image. This is the output of the default parameters of the algorithm on the above shown image. 

Parameters:

_image - A grayscale (CV_8UC1) input image. If only a roi needs to be selected, use: lsd_ptr->detect(image(roi), lines, ...); lines += Scalar(roi.x, roi.y, roi.x, roi.y);

_lines - A vector of Vec4i or Vec4f elements specifying the beginning and ending point of a line. Where Vec4i/Vec4f is (x1, y1, x2, y2), point 1 is the start, point 2 - end. Returned lines are strictly oriented depending on the gradient.

width - Vector of widths of the regions, where the lines are found. E.g. Width of line.

prec - Vector of precisions with which the lines are found. bigger the value, logarithmically better the detection.

• -1 corresponds to 10 mean false alarms
• 0 corresponds to 1 mean false alarm
• 1 corresponds to 0.1 mean false alarms This vector will be calculated only when the objects type is #LSD_REFINE_ADV.

detect

public void detect(Mat _image,
                   Mat _lines,
                   Mat width)

Finds lines in the input image. This is the output of the default parameters of the algorithm on the above shown image. 

Parameters:

_image - A grayscale (CV_8UC1) input image. If only a roi needs to be selected, use: lsd_ptr->detect(image(roi), lines, ...); lines += Scalar(roi.x, roi.y, roi.x, roi.y);

_lines - A vector of Vec4i or Vec4f elements specifying the beginning and ending point of a line. Where Vec4i/Vec4f is (x1, y1, x2, y2), point 1 is the start, point 2 - end. Returned lines are strictly oriented depending on the gradient.

width - Vector of widths of the regions, where the lines are found. E.g. Width of line. bigger the value, logarithmically better the detection.

• -1 corresponds to 10 mean false alarms
• 0 corresponds to 1 mean false alarm
• 1 corresponds to 0.1 mean false alarms This vector will be calculated only when the objects type is #LSD_REFINE_ADV.

detect

public void detect(Mat _image,
                   Mat _lines)

Finds lines in the input image. This is the output of the default parameters of the algorithm on the above shown image. 

Parameters:

_image - A grayscale (CV_8UC1) input image. If only a roi needs to be selected, use: lsd_ptr->detect(image(roi), lines, ...); lines += Scalar(roi.x, roi.y, roi.x, roi.y);

_lines - A vector of Vec4i or Vec4f elements specifying the beginning and ending point of a line. Where Vec4i/Vec4f is (x1, y1, x2, y2), point 1 is the start, point 2 - end. Returned lines are strictly oriented depending on the gradient. bigger the value, logarithmically better the detection.

• -1 corresponds to 10 mean false alarms
• 0 corresponds to 1 mean false alarm
• 1 corresponds to 0.1 mean false alarms This vector will be calculated only when the objects type is #LSD_REFINE_ADV.

drawSegments

public void drawSegments(Mat _image,
                         Mat lines)

Draws the line segments on a given image.

Parameters:

_image - The image, where the lines will be drawn. Should be bigger or equal to the image, where the lines were found.

lines - A vector of the lines that needed to be drawn.

finalize

protected void finalize()
                 throws java.lang.Throwable

Overrides:

finalize in class Algorithm

Throws:

java.lang.Throwable