Collection of functions for extracting quantitative information from images

This submodule contains functions for determining key metrics about an image. Typically these are applied to an image after applying a filter, but a few functions can be applied directly to the binary image.

metrics.boxcount(im[, bins])

Calculates fractal dimension of an image using the tiled box counting method [1]_


Find the length of each chord in the supplied image

metrics.chord_length_distribution(im[, ...])

Determines the distribution of chord lengths in an image containing chords.

metrics.find_h(saturation[, position, srange])

Given a saturation profile, compute the height between given bounds

metrics.lineal_path_distribution(im[, bins, ...])

Determines the probability that a point lies within a certain distance of the opposite phase along a specified direction

metrics.mesh_surface_area([mesh, verts, faces])

Calculate the surface area of a meshed region

metrics.mesh_volume(region[, voxel_size])

Compute the volume of a single region by meshing it

metrics.pc_curve(im[, sizes, pc, seq, ...])

Produces a Pc-Snwp curve given a map of meniscus radii or capillary pressures at which each voxel was invaded

metrics.pc_curve_from_ibip(*args, **kwargs)

This function is deprecated.

metrics.pc_curve_from_mio(*args, **kwargs)

This function is deprecated.

metrics.phase_fraction(im[, normed])

Calculate the fraction of each phase in an image

metrics.pore_size_distribution(im[, bins, ...])

Calculate a pore-size distribution based on the image produced by the porosimetry or local_thickness functions.


Calculates the porosity of an image assuming 1's are void space and 0's are solid phase.

metrics.porosity_profile(im[, axis])

Computes the porosity profile along the specified axis

metrics.prop_to_image(regionprops, shape, prop)

Create an image with each region colored according the specified prop, as obtained by regionprops_3d.


Create a pandas DataFrame containing all the scalar metrics for each region, such as volume, sphericity, and so on, calculated by regionprops_3D.

metrics.radial_density_distribution(dt[, ...])

Computes radial density function by analyzing the histogram of voxel values in the distance transform.

metrics.region_interface_areas(regions, areas)

Calculate the interfacial area between all pairs of adjecent regions

metrics.region_surface_areas(regions[, ...])

Extract the surface area of each region in a labeled image.

metrics.region_volumes(regions[, mode, ...])

Compute volume of each labelled region in an image


Calculates various metrics for each labeled region in a 3D image.


Calculates the porosity of an image as a function subdomain size.

metrics.satn_profile(satn[, s, im, axis, ...])

Computes a saturation profile from an image of fluid invasion

metrics.two_point_correlation(im[, ...])

Calculate the two-point correlation function using Fourier transforms