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ImageMeasurements
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ImageMeasurements

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ImageMeasurements[image,"prop"]

returns the value of property "prop" for the entire image.

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ImageMeasurements[image,"prop",format]

returns the values in the specified output format.

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ImageMeasurements[{image1, image2, …},…]

returns measurements for all imagei.

Details and Options

  • ImageMeasurements works with arbitrary 2D and 3D images.
  • ImageMeasurements[image,{"prop1","prop2",…}] computes multiple properties.
  • ImageMeasurements[image,"Properties"] gives names of all available properties as a list of strings.
  • Position, area, and length measurements are computed in the standard image coordinate system.
  • For images of type "Byte" and "Bit16", ImageMeasurements always normalizes values to lie between 0 and 1.
  • The following properties can be computed on images:
  • Global image properties:
  • "AspectRatio"ratio of height to width
    "Channels"number of image channels
    "ColorSpace"image color space
    "DataRange"range of the underlying data
    "DataType"underlying data type
    "Dimensions"dimensions of the image data
    "ImageDimensions"{width, height} or {width,depth,height} of the image
    "Interleaving"amount of interleaving of the image
    "SampleDepth"number of bits used to represent each pixel
    "Transparency"whether or not the image has an alpha channel
  • Basic histogram properties, measured for each channel separately:
  • "Min"minimum value
    "Max"maximum value
    "MinMax"minimum and maximum values
    "Mean"average value
    "Median"median value
    "StandardDeviation"standard deviation
    "Total"total of all values
  • Basic image intensity properties:
  • "MinIntensity"minimum intensity
    "MaxIntensity"maximum intensity
    "MinMaxIntensity"minimum and maximum intensity
    "MeanIntensity"average intensity
    "MedianIntensity"median intensity
    "StandardDeviationIntensity"standard deviation of the intensity distribution
    "TotalIntensity"total intensity
  • Contour properties:
  • "Contours"lines describing the component boundary
    "ContourHierarchy"topological nesting of the contours
    "PerimeterPositions"sorted positions of the perimeter elements
  • Spatial intensity measurements:
  • "Skew"asymmetry in intensity distribution
    "IntensityCentroid"coordinates of the intensity-weighted centroid
  • Statistical measurements:
  • "Entropy"data entropy (base E)
    "Energy"data energy
  • The following format specifications can be used:
  • Automaticdetermine the output automatically
    "Association"format the result as an Association
    "Dataset"format the result as a Dataset
    "List"format the result as a List
    "RuleList"format the result as a list of Rule expressions
  • ImageMeasurements takes a Masking option. The default setting is Masking->All. The Masking option is ignored when returning global image properties.

Examples

open allclose all

Basic Examples  (2)Summary of the most common use cases

Extract mean color value:

In[1]:=1
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https://wolfram.com/xid/05fos89qur-m5fvfo
In[2]:=2
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https://wolfram.com/xid/05fos89qur-ltosk4
Out[2]=2

Mean pixel intensity:

In[3]:=3
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https://wolfram.com/xid/05fos89qur-mjlrnx
Out[3]=3

Global image entropy:

In[4]:=4
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https://wolfram.com/xid/05fos89qur-d1npoa
Out[4]=4

Standard deviation of pixel intensity in a 3D image:

In[1]:=1
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https://wolfram.com/xid/05fos89qur-p2z0qm
Out[1]=1

Scope  (9)Survey of the scope of standard use cases

Basic Uses  (6)

Test an image to see if it has an alpha channel:

In[1]:=1
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https://wolfram.com/xid/05fos89qur-dq3moz
Out[1]=1

Compute multiple properties of an image:

In[1]:=1
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https://wolfram.com/xid/05fos89qur-czqghs
Out[1]=1

Compute a property of multiple images:

In[1]:=1
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https://wolfram.com/xid/05fos89qur-nir1jp
Out[1]=1

Compute multiple properties of multiple images:

In[1]:=1
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https://wolfram.com/xid/05fos89qur-ja78al
Out[1]=1

Get image dimensions:

In[1]:=1
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https://wolfram.com/xid/05fos89qur-66inls
Out[1]=1

Compare to "Dimensions" property which gives the data dimensions including channels:

In[2]:=2
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https://wolfram.com/xid/05fos89qur-m1bnun
Out[2]=2

Extract pixel value ranges for each channel:

In[1]:=1
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https://wolfram.com/xid/05fos89qur-k0r9v
Out[1]=1

Output Format  (3)

Format the properties as an Association:

In[1]:=1
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https://wolfram.com/xid/05fos89qur-3gz6t4
Out[1]=1

Return a list of rules:

In[1]:=1
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https://wolfram.com/xid/05fos89qur-zxz3gc
Out[1]=1

Return a Dataset:

In[1]:=1
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https://wolfram.com/xid/05fos89qur-yqe5fl
Out[1]=1

Options  (2)Common values & functionality for each option

Masking  (1)

Compute the mean pixel value for a specified region of interest:

In[1]:=1
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https://wolfram.com/xid/05fos89qur-4kvmvm
Out[1]=1

CornerNeighbors  (1)

By default, ImageMeasurements assumes 8-connectivity:

In[1]:=1
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https://wolfram.com/xid/05fos89qur-cs0d8
In[2]:=2
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https://wolfram.com/xid/05fos89qur-koegg
In[3]:=3
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https://wolfram.com/xid/05fos89qur-g1zrhi
Out[3]=3

Use CornerNeighborsFalse to assume 4-connectivity:

In[4]:=4
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https://wolfram.com/xid/05fos89qur-kqaz37
In[5]:=5
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https://wolfram.com/xid/05fos89qur-5zya1f
Out[5]=5

Applications  (5)Sample problems that can be solved with this function

Multiply the gradient magnitude of an image by its maximum value, so that the pixels with the largest values are white:

In[1]:=1
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https://wolfram.com/xid/05fos89qur-2u7yih
Out[1]=1
In[2]:=2
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https://wolfram.com/xid/05fos89qur-xopgc4
Out[3]=3

Detect whether an image has constant pixel values:

In[1]:=1
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https://wolfram.com/xid/05fos89qur-2fefxp
Out[1]=1

Ordinal measurement descriptor of an image:

In[1]:=1
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https://wolfram.com/xid/05fos89qur-3ua00s
In[2]:=2
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https://wolfram.com/xid/05fos89qur-40cxka
Out[2]=2

Compute the centroid distance function for the shapes present in an image:

In[1]:=1
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https://wolfram.com/xid/05fos89qur-42yq2v

Extract the list of shapes from the image:

In[2]:=2
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https://wolfram.com/xid/05fos89qur-sxzk3g
Out[2]=2

Define a function that parametrizes the distance from the contour centroid:

In[3]:=3
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https://wolfram.com/xid/05fos89qur-16223t

Plot the centroid distance function for some of the shapes:

In[4]:=4
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https://wolfram.com/xid/05fos89qur-j4ss2t
Out[4]=4

Define a feature vector sampling the centroid distance:

In[5]:=5
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https://wolfram.com/xid/05fos89qur-ha1zw7

Use the feature vectors to cluster the shapes:

In[6]:=6
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https://wolfram.com/xid/05fos89qur-0bwxrf
Out[6]=6

Compute the Fourier descriptors of a shape:

In[1]:=1
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https://wolfram.com/xid/05fos89qur-je032f

Extract the contour coordinates and compute the Fourier transform of their complex representation:

In[2]:=2
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https://wolfram.com/xid/05fos89qur-med4tp
In[3]:=3
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https://wolfram.com/xid/05fos89qur-eii3bd
In[4]:=4
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https://wolfram.com/xid/05fos89qur-i7a4g2

The original shape can be reconstructed using only a portion of the descriptors:

In[5]:=5
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https://wolfram.com/xid/05fos89qur-nv1wui
In[6]:=6
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https://wolfram.com/xid/05fos89qur-8rgxcj
Out[6]=6

Control the contour smoothness by interactively setting the number of descriptors:

In[7]:=7
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https://wolfram.com/xid/05fos89qur-ggfb7o
Out[7]=7
Wolfram Research (2012), ImageMeasurements, Wolfram Language function, https://reference.wolfram.com/language/ref/ImageMeasurements.html (updated 2022).
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Wolfram Research (2012), ImageMeasurements, Wolfram Language function, https://reference.wolfram.com/language/ref/ImageMeasurements.html (updated 2022).

Text

Wolfram Research (2012), ImageMeasurements, Wolfram Language function, https://reference.wolfram.com/language/ref/ImageMeasurements.html (updated 2022).

✖
Wolfram Research (2012), ImageMeasurements, Wolfram Language function, https://reference.wolfram.com/language/ref/ImageMeasurements.html (updated 2022).

CMS

Wolfram Language. 2012. "ImageMeasurements." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2022. https://reference.wolfram.com/language/ref/ImageMeasurements.html.

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Wolfram Language. 2012. "ImageMeasurements." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2022. https://reference.wolfram.com/language/ref/ImageMeasurements.html.

APA

Wolfram Language. (2012). ImageMeasurements. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/ImageMeasurements.html

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Wolfram Language. (2012). ImageMeasurements. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/ImageMeasurements.html

BibTeX

@misc{reference.wolfram_2025_imagemeasurements, author="Wolfram Research", title="{ImageMeasurements}", year="2022", howpublished="\url{https://reference.wolfram.com/language/ref/ImageMeasurements.html}", note=[Accessed: 19-June-2025 ]}

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@misc{reference.wolfram_2025_imagemeasurements, author="Wolfram Research", title="{ImageMeasurements}", year="2022", howpublished="\url{https://reference.wolfram.com/language/ref/ImageMeasurements.html}", note=[Accessed: 19-June-2025 ]}

BibLaTeX

@online{reference.wolfram_2025_imagemeasurements, organization={Wolfram Research}, title={ImageMeasurements}, year={2022}, url={https://reference.wolfram.com/language/ref/ImageMeasurements.html}, note=[Accessed: 19-June-2025 ]}

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@online{reference.wolfram_2025_imagemeasurements, organization={Wolfram Research}, title={ImageMeasurements}, year={2022}, url={https://reference.wolfram.com/language/ref/ImageMeasurements.html}, note=[Accessed: 19-June-2025 ]}