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ImageLines

ImageLines[image]
finds line segments in image and returns the coordinates of their endpoints.
ImageLines
uses the threshold t for selecting image lines.
ImageLines
uses the parameter d to control the distinctness of the detected lines.
MORE INFORMATION
  • ImageLines returns a list of line segments where the are expressed in the standard image coordinates .
  • ImageLines finds lines in the image whose normalized strength is larger than the specified threshold t.
  • In ImageLines, the parameter d controls how close lines are suppressed. If the value is set to zero, all detected lines are returned. With d set to , only the strongest line may be returned.
  • By default, ImageLines computes lines based on the Hough transform of the image, using the setting Method.
  • Lines are detected by iteratively selecting the strongest peaks in the Hough transform. Using the distinctness parameter, peaks that are within a rectangular range from the already selected peaks are excluded from the set of line candidates.
  • With Method, lines are detected using random sampling. For each sampling, pixels that are within a distance specified by the distinctness parameter d are used for computing the strength of the line. The pixels on the selected line are not used in the following iterations.
  • By default, ImageLines returns lines that span from border to border. With a setting True, detected lines may be divided into smaller segments.
EXAMPLESCLOSE ALL
Basic Examples   (2)
Detect and visualize straight trajectories in a bubble chamber image:
Detect the line going through the foreground pixels:
Detect and visualize straight trajectories in a bubble chamber image:
In[1]:=
Click for copyable input
Out[1]=
 
Detect the line going through the foreground pixels:
In[1]:=
Click for copyable input
Out[1]=
Scope   (2)
Detect segments on a color image:
Specify the distinctness parameter:
Options   (2)
Detect dashed lines in a grayscale image:
Use a random sampling method:
Segmented lines using the random sampling method:
Applications   (3)
Visualize vanishing points:
Detect segments on a gradient magnitude map:
Find wide lines using edge detection:
Possible Issues   (1)
Use the distinctness parameter to prevent detecting duplicated lines:
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