ImageMeasurements [image,"prop"]
returns the value of property "prop" for the entire image.
ImageMeasurements [image,"prop",format]
returns the values in the specified output format.
ImageMeasurements [{image1, image2, …},…]
returns measurements for all imagei.
ImageMeasurements
ImageMeasurements [image,"prop"]
returns the value of property "prop" for the entire image.
ImageMeasurements [image,"prop",format]
returns the values in the specified output format.
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:
-
Automatic determine 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 all close allBasic Examples (2)
Extract mean color value:
Mean pixel intensity:
Global image entropy:
Standard deviation of pixel intensity in a 3D image:
Scope (9)
Basic Uses (6)
Test an image to see if it has an alpha channel:
Compute multiple properties of an image:
Compute a property of multiple images:
Compute multiple properties of multiple images:
Get image dimensions:
Compare to the "Dimensions" property, which gives the data dimensions including channels:
Extract pixel value ranges for each channel:
Output Format (3)
Options (2)
Masking (1)
Compute the mean pixel value for a specified region of interest:
CornerNeighbors (1)
By default, ImageMeasurements assumes 8-connectivity:
Use CornerNeighbors False to assume 4-connectivity:
Applications (5)
Multiply the gradient magnitude of an image by its maximum value, so that the pixels with the largest values are white:
Detect whether an image has constant pixel values:
Ordinal measurement descriptor of an image:
Compute the centroid distance function for the shapes present in an image:
Extract the list of shapes from the image:
Define a function that parametrizes the distance from the contour centroid:
Plot the centroid distance function for some of the shapes:
Define a feature vector sampling the centroid distance:
Use the feature vectors to cluster the shapes:
Compute the Fourier descriptors of a shape:
Extract the contour coordinates and compute the Fourier transform of their complex representation:
The original shape can be reconstructed using only a portion of the descriptors:
Control the contour smoothness by interactively setting the number of descriptors:
History
Introduced in 2012 (9.0) | Updated in 2014 (10.0) ▪ 2015 (10.3) ▪ 2016 (11.0) ▪ 2017 (11.2) ▪ 2022 (13.1)
Text
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.
APA
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: 16-November-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: 16-November-2025]}