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ImageSegmentationFilter[image,marker]

segments part of image specified by marker and returns an image mask.

Details and Options
Details and Options Details and Options
Examples  
Basic Examples  
Scope  
Options  
PerformanceGoal  
Applications  
See Also
Related Guides
History
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ImageSegmentationFilter

ImageSegmentationFilter[image,marker]

segments part of image specified by marker and returns an image mask.

Details and Options

  • ImageSegmentationFilter segments objects or components of interest in an image and returns it as a single-channel image. It is also known as image matting and foreground separation.
  • The following marker specifications can be given:
  • possegments the component containing the position pos
    {pos1,pos2,…}segments the component containing all posi
    Rectangle[…]segments the component indicated by a bounding box
  • The following options can be given:
  • PerformanceGoal Automaticaspects of performance to try to optimize
    TargetDevice"CPU"the target device on which to perform training
  • Possible settings for PerformanceGoal include:
  • Automaticautomatic tradeoff between speed and quality
    "Balanced"medium quality for average speed
    "Quality"optimize for quality of final results
    "Speed"optimize for speed of getting results

Examples

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Basic Examples  (2)

Get a mask for an object specified by a point:

Wolfram Language code: ImageSegmentationFilter[[image], {700, 200}]

Get a mask for a segment specified by a bounding box:

Wolfram Language code: img = [image];
Wolfram Language code: HighlightImage[img, Rectangle[{260, 135}, {680, 530}]]
Wolfram Language code: ImageSegmentationFilter[img, Rectangle[{260, 135}, {680, 530}]]

Scope  (1)

Use different markers to specify the objects to segment:

Wolfram Language code: img = [image];

Use a single point:

Wolfram Language code: HighlightImage[img, {100, 80}]
Wolfram Language code: ImageSegmentationFilter[img, {100, 80}]

Use multiple points as markers:

Wolfram Language code: HighlightImage[img, {Green, {{100, 80}, {160, 120}}}]

Get the mask:

Wolfram Language code: ImageSegmentationFilter[img, {{100, 80}, {160, 120}}]

Use a rectangle as a marker:

Wolfram Language code: HighlightImage[img, Rectangle[{60, 30}, {130, 150}]]

Get the mask:

Wolfram Language code: ImageSegmentationFilter[[image], Rectangle[{60, 30}, {130, 150}]]

Highlight the image with the computed mask:

Wolfram Language code: HighlightImage[img, %]

Options  (1)

PerformanceGoal  (1)

Compare the result using "Speed":

Wolfram Language code: ImageSegmentationFilter[[image], Rectangle[{0, 0}, {120, 80}], PerformanceGoal -> "Speed"]//AbsoluteTiming

Compare the result using "Quality":

Wolfram Language code: ImageSegmentationFilter[[image], Rectangle[{0, 0}, {120, 80}], PerformanceGoal -> "Quality"]//AbsoluteTiming

Applications  (2)

Find a mask based on an image segment:

Wolfram Language code: i = [image]; ImageSegmentationFilter[i, {100, 60}]

Blur the background to focus on the object of interest:

Wolfram Language code: ImageCompose[Blur[i, 5], SetAlphaChannel[i, %]]

Segmenting a person in a Toulouse-Lautrec painting:

Wolfram Language code: painting = [image];
Wolfram Language code: HighlightImage[painting, {White, Rectangle[{420, 353}, {570, 710}]}]
Wolfram Language code: ImageSegmentationFilter[painting, Rectangle[{420, 353}, {570, 710}]]
Wolfram Research (2024), ImageSegmentationFilter, Wolfram Language function, https://reference.wolfram.com/language/ref/ImageSegmentationFilter.html.

Text

Wolfram Research (2024), ImageSegmentationFilter, Wolfram Language function, https://reference.wolfram.com/language/ref/ImageSegmentationFilter.html.

CMS

Wolfram Language. 2024. "ImageSegmentationFilter." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/ImageSegmentationFilter.html.

APA

Wolfram Language. (2024). ImageSegmentationFilter. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/ImageSegmentationFilter.html

BibTeX

@misc{reference.wolfram_2026_imagesegmentationfilter, author="Wolfram Research", title="{ImageSegmentationFilter}", year="2024", howpublished="\url{https://reference.wolfram.com/language/ref/ImageSegmentationFilter.html}", note=[Accessed: 05-October-2026]}

BibLaTeX

@online{reference.wolfram_2026_imagesegmentationfilter, organization={Wolfram Research}, title={ImageSegmentationFilter}, year={2024}, url={https://reference.wolfram.com/language/ref/ImageSegmentationFilter.html}, note=[Accessed: 05-October-2026]}