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Updated: Jun 20, 2026

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

Published on: January 5, 2024

Application of edge detection method based on image quality gradient for twin detection.

D Chen¹, G-T Lui, J-C Kuo

¹Department of Materials Science and Engineering, National Cheng Kung University, Tainan, Taiwan.

Journal of Microscopy

|September 24, 2009

Summary

A new image quality method quantitatively analyzes electrodeposited copper twinning. This technique offers a higher twin density measurement than traditional Orientation Imaging Microscopy (OIM) analysis.

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Last Updated: Jun 20, 2026

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

Image Recognition and Parameter Analysis of Concrete Vibration State Based on Support Vector Machine

Published on: January 5, 2024

Area of Science:

Materials Science
Crystallography
Surface Science

Background:

Electrodeposited copper is crucial in various electronic applications.
Understanding copper twinning is essential for optimizing material properties.
Existing methods for analyzing twinning have limitations.

Purpose of the Study:

To develop and validate a novel image quality-based method for quantitative analysis of electrodeposited copper twinning.
To compare the effectiveness of the new method against established techniques like Orientation Imaging Microscopy (OIM).

Main Methods:

The study employed an image quality-based approach utilizing electron backscattering diffraction (EBSD) data.
Key processes included hexagonal edge detection, a thinning algorithm, and twin determination.
The developed algorithm was used to calculate twin density.

Main Results:

The new algorithm determined a twin density of 65.61% in electrodeposited copper.
This result is significantly higher than the 57.44% twin density obtained via conventional OIM analysis.
The findings highlight the sensitivity of the new method.

Conclusions:

The developed image quality-based algorithm provides a reliable and potentially more accurate alternative for detecting twin boundaries in electrodeposited copper.
This method enhances quantitative analysis of crystallographic features.
Further research can explore its application in other metallic systems.