### G-Tortuosity

Graph-based tortuosity proposes a new way of calculation of the M-tortuosity descriptor [1]. This algorithm is based on the PNP method [2] to extract pores and construct a graph from the porous phase of a binary microstructure. Through this scheme, pores are the nodes, distances between pores are the arcs between...

### Pore network partitioning (PNP-2D/3D)

The pore network partitioning PNP is an efficient algorithm that allows the extraction of the pore network structure of a binary microstructure. It involves a distance map compuation in order to extract maxima points, a filtering process to generate different types of pores and a geodesic distance transform with...

### 2D surface rendering

2D surface rendering on the CPU. The algorithm creates a 3D volume from intensity values then uses fast point projection and gradient calculation to give the impression of the visualization of an iso-surface with several 3D effects such as shadow and distance focus. A texture from another image can be mapped on the...

### 3D iso-surface rendering

3D iso-surface rendering on the CPU. The algorithm uses fast point projection and gradient calculation to give the impression of the visualization of an iso-surface with several 3D effects such as shadow and distance focus. The orientation of the volume can be changed by moving the mouse with right click and hold.

### Segmentation and detection of overlapped ellipses in binary images

This plugin proposes a complete method for recognizing and measuring highly overlapping ellipses in binary images. Starting from a binary image (the ellipses to be detected must be white on a black background), the pattern recognition process consists of the following successive steps: i) identification of all the...

### BM3D Block matching and 3D filtering

BM3D (Block matching and 3D filtering) [1] is still today a reference algorithm for noise reduction. It is based on a splitting of the image into patches, a grouping of similar patches, a 2D filter in the patch domain, a 1D filter in the similarity domain, and then an inversion of these filters to reconstruct the...

### Colored dead leaves random model of spheres

Dead leaves random models [Matheron 1968] are used to simulate images with objects partly overlapping other objects. These processes are used for instance to model powders and estimate their composition or size distribution. This plugin allows simulations of spheres multicomponent version scheme [Jeulin, 1997]....

### H-tortuosity-by-iterative-erosions (3D)

H-tortuosity-by-iterative-erosions for the characterization of 3D volumes: Computation of the H-tortuosity estimator of the microstructure, as seen by a spherical particle of given size. In addition to keeping the properties of the H-tortuosity, this descriptor is linked to the notion of constrictivity, characterizing...

### H-tortuosity-by-iterative-erosions (2D)

H-tortuosity-by-iterative-erosions for the characterization of 2D images: Computation of the H-tortuosity estimator of the microstructure, as seen by a spherical particle of given size. In addition to keeping the properties of the H-tortuosity, this descriptor is linked to the notion of constrictivity, characterizing...

### H-tortuosity (3D)

Computation of the H-tortuosity estimator for the characterization of 3D volumes: a scalable topological descriptor providing a 3D map of mean tortuosities and final scalar values, the H-scalars, assessing the average variations of the morphological tortuosity with the scale.. This descriptor is based on a Monte Carlo...

### H-tortuosity (2D)

Computation of the H-tortuosity estimator for the characterization of 2D images: a scalable topological descriptor providing a 2D map of mean tortuosities and final scalar values, the H-scalars, assessing the average variations of the morphological tortuosity with the scale. This descriptor is based on a Monte Carlo...

### M-tortuosity-by-iterative-erosions (2D)

M-tortuosity-by-iterative-erosions for the characterization of 2D images: Computation of the M-tortuosity estimator of the microstructure, as seen by a spherical particle of given size. In addition to keeping the properties of the M-tortuosity, this descriptor is linked to the notion of constrictivity, characterizing...

### M-tortuosity (2D)

Computation of the M-tortuosity estimator for the characterization of 2D images: a scalable topological descriptor providing a 2D map of mean tortuosities, a set of M-coefficients, of which the histogram is meaningful, and a final scalar value, the M-scalar, assessing the geometric tortuosity of the overall...

### Deterministic M-tortuosity (3D)

Deterministic version of the M-tortuosity with imposed starting points set, for the characterization of 3D volumes. Real images, from electron tomography for instance, with a meaningless void can be described now. More details can be found using the links below. 23/09/20: bugs correction 29/09/20: update

### Deterministic M-tortuosity (2D)

Deterministic version of the M-tortuosity with imposed starting points set, for the characterization of 2D images. Real images, from electron tomography for instance, with a meaningless void can be described now. More details can be found using the links below. 23/09/20: bugs correction 29/09/20: update

### Edge-preserving filter

Noise reduction of a grayscale image preserving the sharp edges of objects. Is based initially on the work of Kuwahara, then Schulze and Pearce. In contrast to the latter, which retain for a given point, the local mean of the lowest variance, a linear combination of the local means in the vicinity is held according to...

### 3D surface area

3D surface area measurement of object(s) inside a volume. Each connected components can be consider as one object, or the entire volume as only one object. The calculation is from [Lindblad, 2005] : the estimation is performed with a “marching cube” approach using local weights. Two kind of local weights are...

### Negative

Compute the negative of an 8-bit grayscale image or volume.

### Extract ROI from binary mask

Extract the region of interest (ROI) of an image using a binary image (supported formats are .bmp, .png, .jpg, .tiff, and .fda). The region of interest is extracted within a new image of the same size as the original image. Outside the region of interest, the intensity values are zero. Zero intensity values from the...

### SAXS intensity from projection

Small Angle X-ray Scattering intensity computed from projections of a 3D volume. Projections should be of size of power of two. The computed diagram is proportional to the square of the Fourier transform modulus of the projection of the object along one axis. The calculation is prone to strong finite size effects....

### Projection

Orthogonal projection of a volume along x-axis, y-axis, or z-axis. This plugin can compute also opaque projection.

### Extraction of porosity

Extraction of porosity from binary image taking into account external roughness. This plugin operates with a morphological closing by a disc whose radius can be automatically estimated, followed by a geodesic morphological opening. This method is defined and used in [Moreaud et al. 2008].

### Extract patches from image

Extract patches from image using graphical interface. Update: 200200923: adding normalization for 8 bits or 24bits RGB image.

### Rugosity analysis

Rugosity / texture analysis by H-maxima and area of influences on zones of interest drawn over the image. Computation of local maxima or minima, then area of influence, and for each area of influence, extraction of the surface area, minimum, and maximum intensity values. The zones of interest are directly defined by...

### Homogeneization Dielectric Permittivity FFT scheme

An efficient method to solve the problem of homogenization of physical properties of heterogeneous media, such as dielectric permittivity, is the implementation of numerical solutions, before estimating the effective properties by spatial average of the solution. The input data is a 3D binary volume or a 2D binary...

### Get plane

Extract cut plane(s) of a volume. Update 20210223: add atlas extraction and extraction of all cut planes along one axis can be saved in TIFF or PNG format. Update 20200423: extraction of all cut planes along one axis.

### Histogram

Compute the histogram of an image.

### ARFBF Morphological Analysis

In the case of active phases observable in the form of stacked sheets, the classic strategy is to segment these sheets individually and characterize their length or curvature [Celse, 2008], which may related to actibity [Gandubert, 2006]. Since the images are quite noisy at this level of resolution, this type of...

### Mathematical morphology binary geodesic operations 2D and 3D

Mathematical morphology has been introduced by Matheron and Serra [Serra, 1982] in the late 1960's. It defines among others, two basic operators: dilation and erosion. These tools and their combinations are powerful and widespread for filtering and image analysis. For instance, operations such as opening, closing are...

### Workshop GdR NanOperando 2019

A workshop dedicating to the potential of plug im! platform to extract quantitative information from data from in situ experiments, therefore "dynamic" by nature! Includes a package with a set of plug im! modules, working data files, and pdf slides to guide users.