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ImageLines
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ImageLines

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ImageLines[image]

finds line segments in image and returns the coordinates of their endpoints.

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ImageLines[image,t]

uses the threshold t for selecting image lines.

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ImageLines[image,t,d]

uses the parameter d to control the distinctness of the detected lines.

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ImageLines[video,…]

finds lines in frames of video.

Details and Options

  • ImageLines returns a list of line segments in the form Line[{p1,p2}], where each pi={xi,yi} is expressed in the standard image coordinate system.
  • ImageLines[image,t] finds lines in the image whose normalized strength is larger than the specified threshold t.
  • ImageLines sorts the result based on the normalized strength.
  • In ImageLines[image,t,d], 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 1, only the strongest line may be returned.
  • The following options can be given:
  • MaxFeatures Allmaximum number of features to return
    Method "Hough"method to detect lines
  • With a setting MaxFeatures->n, at most n lines with largest normalized strength are returned.
  • Possible line detection methods are:
  • "Hough"lines based on Hough transform (default)
    "RANSAC"lines using the RANSAC algorithm
  • With Method->"Hough", 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->"RANSAC", 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 Method->{"Segmented"->True}, detected lines may be divided into smaller line segments.

Examples

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Basic Examples  (1)Summary of the most common use cases

Detect and visualize straight lines in an image:

In[1]:=1
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https://wolfram.com/xid/0bdpj8gfc-vebnjt
Out[2]=2

Highlight detected lines:

In[3]:=3
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https://wolfram.com/xid/0bdpj8gfc-zxawlm
Out[3]=3

Scope  (2)Survey of the scope of standard use cases

Specify the distinctness parameter:

In[1]:=1
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https://wolfram.com/xid/0bdpj8gfc-c7kt2l
Out[1]=1

Detect the line going through the foreground pixels:

In[1]:=1
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https://wolfram.com/xid/0bdpj8gfc-turx51
Out[1]=1

Options  (3)Common values & functionality for each option

MaxFeatures  (1)

Specify the maximum number of lines to be to be detected:

In[1]:=1
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https://wolfram.com/xid/0bdpj8gfc-jufd9k
Out[2]=2
In[3]:=3
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https://wolfram.com/xid/0bdpj8gfc-vr5fug
Out[3]=3

Method  (2)

By default, lines are detected using Method->"Hough":

In[1]:=1
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https://wolfram.com/xid/0bdpj8gfc-bwc8u8
Out[3]=3

Use a random sampling method:

In[4]:=4
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https://wolfram.com/xid/0bdpj8gfc-zfh1u
Out[5]=5

Detect segmented lines in a grayscale image:

In[1]:=1
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https://wolfram.com/xid/0bdpj8gfc-nx8df9
Out[1]=1

Segmented lines using the random sampling method:

In[2]:=2
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https://wolfram.com/xid/0bdpj8gfc-b1yld3
Out[2]=2

Applications  (6)Sample problems that can be solved with this function

Detect and visualize straight trajectories in a bubble chamber image:

In[1]:=1
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https://wolfram.com/xid/0bdpj8gfc-oooixa
Out[3]=3

Detect segments on a color image:

In[1]:=1
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https://wolfram.com/xid/0bdpj8gfc-bs5cho
Out[1]=1

Visualize vanishing points:

In[1]:=1
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https://wolfram.com/xid/0bdpj8gfc-rhcawx
Out[1]=1

Detect segments on a gradient magnitude map:

In[1]:=1
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https://wolfram.com/xid/0bdpj8gfc-i5daaj
Out[1]=1

Find wide lines using edge detection:

In[1]:=1
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https://wolfram.com/xid/0bdpj8gfc-qyt3kj
Out[1]=1

Straighten the tower of Pisa:

In[1]:=1
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https://wolfram.com/xid/0bdpj8gfc-xul6sp

Compute the gradient of the image to highlight edges:

In[2]:=2
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https://wolfram.com/xid/0bdpj8gfc-d74o90
Out[2]=2

Find the most significant straight lines in the gradient image:

In[3]:=3
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https://wolfram.com/xid/0bdpj8gfc-ksf7ok
Out[3]=3

FInd the angles corresponding to each line:

In[4]:=4
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https://wolfram.com/xid/0bdpj8gfc-x1b2ro
Out[4]=4

Compute the average angle of the vertical lines:

In[5]:=5
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https://wolfram.com/xid/0bdpj8gfc-galyh3
Out[5]=5

Rotate the image by to make almost-vertical lines vertical:

In[6]:=6
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https://wolfram.com/xid/0bdpj8gfc-d92u8p
Out[6]=6

Possible Issues  (2)Common pitfalls and unexpected behavior

Use the distinctness parameter to prevent detecting duplicated lines:

In[1]:=1
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https://wolfram.com/xid/0bdpj8gfc-wk6kke
Out[1]=1

Thin lines in binary images might not be correctly detected:

In[1]:=1
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https://wolfram.com/xid/0bdpj8gfc-ws33ge
In[2]:=2
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https://wolfram.com/xid/0bdpj8gfc-uobb4o
Out[2]=2

Blurring the image typically improves line detection:

In[3]:=3
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https://wolfram.com/xid/0bdpj8gfc-pj5zaq
Out[3]=3

Rescaling the image to a larger size might also help in some cases:

In[4]:=4
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https://wolfram.com/xid/0bdpj8gfc-6dd29u
In[5]:=5
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https://wolfram.com/xid/0bdpj8gfc-79ihex
Out[5]=5
Wolfram Research (2010), ImageLines, Wolfram Language function, https://reference.wolfram.com/language/ref/ImageLines.html (updated 2025).
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Wolfram Research (2010), ImageLines, Wolfram Language function, https://reference.wolfram.com/language/ref/ImageLines.html (updated 2025).

Text

Wolfram Research (2010), ImageLines, Wolfram Language function, https://reference.wolfram.com/language/ref/ImageLines.html (updated 2025).

✖
Wolfram Research (2010), ImageLines, Wolfram Language function, https://reference.wolfram.com/language/ref/ImageLines.html (updated 2025).

CMS

Wolfram Language. 2010. "ImageLines." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2025. https://reference.wolfram.com/language/ref/ImageLines.html.

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Wolfram Language. 2010. "ImageLines." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2025. https://reference.wolfram.com/language/ref/ImageLines.html.

APA

Wolfram Language. (2010). ImageLines. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/ImageLines.html

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Wolfram Language. (2010). ImageLines. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/ImageLines.html

BibTeX

@misc{reference.wolfram_2025_imagelines, author="Wolfram Research", title="{ImageLines}", year="2025", howpublished="\url{https://reference.wolfram.com/language/ref/ImageLines.html}", note=[Accessed: 27-April-2025 ]}

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@misc{reference.wolfram_2025_imagelines, author="Wolfram Research", title="{ImageLines}", year="2025", howpublished="\url{https://reference.wolfram.com/language/ref/ImageLines.html}", note=[Accessed: 27-April-2025 ]}

BibLaTeX

@online{reference.wolfram_2025_imagelines, organization={Wolfram Research}, title={ImageLines}, year={2025}, url={https://reference.wolfram.com/language/ref/ImageLines.html}, note=[Accessed: 27-April-2025 ]}

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@online{reference.wolfram_2025_imagelines, organization={Wolfram Research}, title={ImageLines}, year={2025}, url={https://reference.wolfram.com/language/ref/ImageLines.html}, note=[Accessed: 27-April-2025 ]}