Method and apparatus for analyzing the structure of composite materials, and program thereof.

Abstract

To provide a method for analyzing a relation among a process, a composite material structure, and a composite material characteristic by creating an image set regionally divided with the same reference so as to quantify a difference in a morphological feature amount between regionally divided images for comparison.SOLUTION: An analyzing method for a structure shape of a composite material formed of two or more kinds of materials includes the steps of: inputting an image set including a plurality of two-dimensional images in which K-dimensional vectors are allocated for each pixel (S1); creating a data set in which the K-dimensional vectors of the two-dimensional images included in the image set are stacked (S2); creating a clustering result by performing clustering on the data set at the respective data points having the similar K-dimensional vectors (S3); creating a regionally divided image set in which the K-dimensional vectors of each pixel of the image set are replaced in a class on the basis of the clustering result (S4); and outputting the regionally divided image set (S5).EFFECT: A change in structure shape in the image set can be quantified, and thus a relation among a process, a composite material structure, and a composite material characteristic can be analyzed.SELECTED DRAWING: Figure 1

Claims

1. A method for analyzing the microstructure of a composite material consisting of two or more materials, Input an image set containing multiple 2D images, each with a K-dimensional vector assigned to it. A dataset is created by stacking the K-dimensional vectors of the two-dimensional images included in the aforementioned image set. The aforementioned dataset is clustered by grouping data points with similar K-dimensional vectors to create clustering results. Based on the clustering results, a region-partitioned image set is created by replacing the K-dimensional vector of each pixel in the image set with a class. Output the aforementioned region segmentation image set, The aforementioned image set is characterized in that a K-dimensional vector is assigned to each pixel of the two-dimensional image from signal information obtained by the interaction between the probe and the sample surface, and is a method for analyzing the structure of a composite material.

2. A method for analyzing the microstructure of a composite material made of two or more materials, Input an image set containing multiple 2D images, each with a K-dimensional vector assigned to it. A dataset is created by stacking the K-dimensional vectors of the two-dimensional images included in the aforementioned image set. The aforementioned dataset is clustered by grouping data points with similar K-dimensional vectors to create clustering results. Based on the clustering results, a region-partitioned image set is created by replacing the K-dimensional vector of each pixel in the image set with a class. Output the aforementioned region segmentation image set, A method for analyzing the structure of a composite material, characterized by using the aforementioned set of segmented images, calculating the geometric features of the segmented images, and outputting the geometric features of the segmented images.

3. In the method for analyzing the structure of a composite material according to claim 2, The aforementioned image set is a method for analyzing the structure of a composite material, characterized in that a sample is irradiated with charged particle beams or X-rays, and a K-dimensional vector is assigned to each pixel of a two-dimensional image from the spectral information of the X-rays or charged particle beams generated from the sample.

4. In the method for analyzing the structure of a composite material according to claim 2, A method for analyzing the structure of a composite material, characterized in that the shape features of the region segmented image are the area ratios of the regions.

5. In the method for analyzing the structure of a composite material according to claim 2, The creation of the aforementioned clustering results is as follows: Normalize each vector component, Compress the dimension of the vector components, Perform clustering. A method for analyzing the structure of composite materials, characterized by the following features.

6. In the method for analyzing the structure of a composite material according to claim 5, A method for analyzing the structure of a composite material, characterized in that the dimensionality reduction of the vector components is performed by principal component analysis.

7. An image set input unit that inputs an image set containing multiple two-dimensional images to which a K-dimensional vector is assigned to each pixel, An input dataset creation unit creates a dataset by stacking K-dimensional vectors of two-dimensional images included in the aforementioned image set, A clustering result creation unit creates clustering results by clustering the aforementioned dataset with data points that have similar K-dimensional vectors, A region segmentation image set creation unit creates a region segmentation image set by replacing the K-dimensional vector of each pixel in the image set with a class based on the clustering results, An output unit that outputs the aforementioned region segmentation image set, The system includes a shape feature calculation unit that uses the aforementioned set of segmented images to calculate the shape features of the segmented images, The composite material structure analysis device is characterized in that the output unit outputs the geometric feature quantities of the region segmented image.

8. In the composite material structure analysis apparatus according to Claim 7, The composite material structure analysis device is characterized in that the shape features of the region segmentation image are the area ratios of the regions.

9. In the composite material structure analysis apparatus according to claim 7, The clustering result creation unit, Normalize each vector component, Compress the dimension of the vector components, An analytical device for the structure of composite materials, characterized by its ability to perform clustering.

10. In the composite material structure analysis apparatus according to claim 9, The composite material structure analysis device is characterized in that the dimensionality reduction of the vector components is performed by principal component analysis.

11. A program that causes a computer to function as an analysis device for the structure of a composite material, An image set input unit that inputs an image set containing multiple two-dimensional images, each with a K-dimensional vector assigned to a pixel, An input dataset creation unit creates a dataset by stacking K-dimensional vectors of two-dimensional images included in the aforementioned image set, A clustering result creation unit creates clustering results by clustering the aforementioned dataset with data points that have similar K-dimensional vectors, A region segmentation image set creation unit creates a region segmentation image set by replacing the K-dimensional vector of each pixel in the image set with a class based on the clustering results, An output unit that outputs the aforementioned region segmentation image set, Using the aforementioned set of segmented images, it functions as a shape feature calculation unit that calculates the shape features of the segmented images. A program characterized in that the output unit outputs the geometric feature quantities of the region segmented image.

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