DREAM.3D v6 User Manual
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Statistics (Morphological)
This Filter calculates the second-order moments of each Feature in order to determine the principal axis lengths, pricipal axis directions, aspect ratios and moment invariant Omega3s. The principal axis lengths are those of a "best-fit" ellipsoid. The algorithm for determining the moments and these values is as follows:
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Image
Kind | Default Name | Type | Component Dimensions | Description |
---|---|---|---|---|
Cell Attribute Array | FeatureIds | int32_t | (1) | Specifies to which Feature each Cell belongs |
Feature Attribute Array | Centroids | float | (3) | X, Y, Z coordinates of Feature center of mass |
Attribute Matrix | CellFeatureData | Cell Feature | N/A | Feature Attribute Matrix of the selected Feature Ids |
Kind | Default Name | Type | Component Dimensions | Description |
---|---|---|---|---|
Feature Attribute Array | AspectRatios | float | (2) | Ratio of axis lengths (b/a and c/a) for best-fit ellipsoid to Feature |
Feature Attribute Array | AxisEulerAngles | float | (3) | Euler angles (in radians) necessary to rotate the sample reference frame to the reference frame of the Feature, where the prinicpal axes of the best-fit ellipsoid are (X, Y, Z) |
Feature Attribute Array | AxisLengths | float | (3) | Axis lengths (a, b, c) for best-fit ellipsoid to Feature |
Feature Attribute Array | Omega3s | float | (1) | 3rd invariant of the second-order moment matrix for the Feature, does not assume a shape type (i.e., ellipsoid) |
[1] Representation and Reconstruction of Three-dimensional Microstructures in Ni-based Superalloys, AFOSR FA9550-07-1-0179 Final Report, 20 Dec 2010.
[2] On the use of moment invariants for the automated classifcation of 3-D particle shapes, J. MacSleyne, J.P. Simmons and M. De Graef, Modeling and Simulations in Materials Science and Engineering, 16, 045008 (2008).
[3] n-Dimensional Moment Invariants and Conceptual Mathematical Theory of Recognition n-Dimensional Solids, Alexander G. Mamistvalov, IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. 20, NO. 8, AUGUST 1998, p. 819-831.
[4] M. Groeber, M. Uchic, D. Dimiduk, and S. Ghosh. “A Framework for Automated Analysis and Simulation of 3D Polycrystalline Microstructures, Part 1: Statistical Characterization” Acta Materialia, 56 (2008), 1257-1273.
Please see the description file distributed with this Plugin
If you need more help with a Filter, please consider asking your question on the DREAM.3D Users Google group!