ImageSegmentationComponents

ImageSegmentationComponents[image]

performs a global segmentation of image and returns a label matrix of components.

ImageSegmentationComponents[image,spec]

segments an image into components based on the given spec.

Details and Options

  • ImageSegmentationComponents is a high-level image segmentation that can either segment the whole image or segment specified objects and components in an image.
  • The following specifications spec can be given:
  • possegments a component specified by an {x,y} coordinate
    {pos1,pos2,}attempts to segment the image into components corresponding to every posi
    {{pos11,pos12,},{pos21,},}specify each component with a list of positions
    Rectangle[]specify each component with a bounding box
    {Rectangle[],Rectangle[],}a list of bounding boxes, one for each component
  • When multiple positions or rectangles are provided, a segment is computed for every marker. If different markers generate significantly overlapping components, the less dominant segment will be suppressed.
  • 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  (1)

Segment an image:

Scope  (3)

Segment an image and colorize the segments:

Highlight segments on the image:

Generate a mask for a segment indicated by a list of positions:

Highlight the specified target points as well as the segmentation on the image:

Generate a mask for a segment inside a bounding box:

Highlight the bounding box as well as the segmentation on the image:

Options  (1)

PerformanceGoal  (1)

By default, a medium-speed model with moderate quality is used:

Aim for speed, but this typically results in lower quality:

Aim for high quality, but this typically leads to slower results:

Applications  (3)

Segment repeating components in an image:

Segment an x-ray or other image modalities:

Segment a region selected by points:

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

Text

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

CMS

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

APA

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

BibTeX

@misc{reference.wolfram_2024_imagesegmentationcomponents, author="Wolfram Research", title="{ImageSegmentationComponents}", year="2024", howpublished="\url{https://reference.wolfram.com/language/ref/ImageSegmentationComponents.html}", note=[Accessed: 01-December-2024 ]}

BibLaTeX

@online{reference.wolfram_2024_imagesegmentationcomponents, organization={Wolfram Research}, title={ImageSegmentationComponents}, year={2024}, url={https://reference.wolfram.com/language/ref/ImageSegmentationComponents.html}, note=[Accessed: 01-December-2024 ]}