Material Formation Image Analysis via Fourier Transform and EM Algorithm

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Solution Overview

Problem

Conventional microscope examination processes for determining crystal grain sizes in steel are time-consuming and labor-intensive, making it inefficient to obtain a size distribution of structures forming a material from formation images.

Innovation Solution

An information processing device and method that acquires a material formation image, applies a Fourier transform to generate a power spectrum, and employs the expectation-maximization algorithm to efficiently calculate the size distribution of structures, potentially using contrast images with different levels of contrast to enhance accuracy.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If conventional microscope examination processes are used to determine crystal grain sizes, then measurement accuracy is maintained, but time consumption and labor requirements increase significantly

Engineering Contradiction:

Improveprocessing speedVSAvoidtime consumption

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The patent replaces the manual mechanical measurement process with an automated image processing system that uses Fourier transform and expectation-maximization algorithms to automatically determine grain size distribution from microscopic images, eliminating manual intervention and significantly reducing processing time

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent transforms the measurement approach by changing from direct spatial domain measurement to frequency domain analysis using Fourier transform, and employs the expectation-maximization algorithm to iteratively optimize grain size parameter estimation, achieving both speed and accuracy

Inventive Principle:

Principle #35Parameter changes

2Measurement precision

If conventional microscope examination processes are used to determine crystal grain sizes, then measurement precision is maintained, but labor requirements increase

Engineering Contradiction:

Improvegrain size measurement accuracyVSAvoidlabor intensity

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The system performs self-service by automatically processing images through the Fourier transform and expectation-maximization algorithm without requiring manual measurement operations, making the process effortless while maintaining precision through rigorous mathematical computation

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Manual measurement operations are replaced with automated computational algorithms that objectively analyze image data, eliminating subjective human factors and reducing labor intensity while preserving measurement accuracy through systematic mathematical processing

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If Fourier transform and expectation-maximization algorithm are used to generate size distribution, then processing efficiency is improved, but computational complexity increases

Engineering Contradiction:

Improveprocessing efficiencyVSAvoidcomputational complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent transitions from direct spatial domain image analysis to frequency domain analysis using Fourier transform, adding a dimensional transformation that simplifies the extraction of size distribution characteristics and enables more efficient computational processing

Inventive Principle:

Principle #17Another dimension (Dimensionality change)

Solution Approach 2:

The Fourier transform is applied as a preliminary step to convert the image to the frequency domain before applying the expectation-maximization algorithm, preparing the data in advance to facilitate more efficient and accurate size distribution calculation

Inventive Principle:

Principle #10Preliminary action

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

Enables the efficient and accurate determination of size distributions of structures from material formation images, reducing the time and labor required for analysis.

Implementation Method 1

generates a Fourier transform result representing a power spectrum by applying a Fourier transform to the material formation image

Methodology Applied

Scientific EffectFourier transform:

Data Source

PatentUS11640674B2Information processing device, information processing method, and storage medium storing information processing program

Publication Date: 2023.05.02 TOYOTA JIDOSHA KK

AI summary

An information processing device acquires a material formation image representing a formation of a material, the material formation image being obtained by imaging the material. The information processing device generates a Fourier transform result representing a power spectrum by applying a Fourier transform to the acquired material formation image. The information processing device, on the basis of the Fourier transform result of the material formation image, employs an expectation-maximization algorithm to generate a size distribution of structures forming the material.