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ImageJ

ImageJは、アメリカ国立衛生研究所（NIH）によって開発されたオープンソースのJavaベースの画像処理ソフトウェアであり、生物学や医学研究をはじめとする科学的画像データの解析に広く使用されている。このプラットフォームは、顕微鏡画像、時間経過画像、医療画像など、多様な画像タイプの処理と分析をサポートし、閾値設定、フィルタリング、物体のカウント、距離測定などの基本的な画像処理機能から定量的データ分析までを行うことができる。ImageJの大きな特徴はその拡張性であり、ユーザーが開発したプラグインやマクロを通じて機能をカスタマイズできるため、研究者にとって非常に柔軟なツールとなっている。

Review

2024/08/29

Trial of ImageJ

MatDaCs Tool Trial Report: WebPlotDigitizer

1. Introduction

This time, I tried using “WebPlotDigitizer,” a tool listed on MatDaCs. This tool extracts data from images, making it a very useful tool for digitizing experimental and computational data graphs.

2. Tool Overview

Provider: Automeris.io

Purpose: Digitizing data from images

Main Features:

Automatic, semi-automatic, and manual data extraction modes
Easy-to-use interface
Multifunctionality

3. How to Use

3.1 Installation

It can be used as a web application from the official site.

3.2 Basic Operation

Upload an image
Define the axes
Select data points
Export the data

4. User Experience

4.1 Ease of Use

The intuitive interface made it easy for even beginners to use. The explanation video on the official page was also easy to follow.

4.2 Accuracy

Even in automatic extraction mode, it demonstrates high accuracy.

5. Use Case

5.1 Preparing the Image

This time, I extracted the specific heat calculation data for the one-dimensional Heisenberg model. The data was taken from Fig.8(a) of this paper (K. Ido et al, Comp. Phys. Commun. 298, 109093 (2024)). The raw data of this calculation is also available from the following repository (ISSP Data Repository), so the accuracy of the extracted data can be verified.

5.2 Accessing WebPlotDigitizer

Go to WebPlotDigitizer and click “Launch App.”

5.3 Uploading the Image

Take a screenshot of the figure from the paper and upload that image.

5.4 Defining the Axes

Select “2D (X-Y) Plot” and define the axes.

5.5 Extracting Data Points

Select data points using “Add point.” Add points like the figure below. A zoomed-in view will appear in the top-right corner, which you can also use as a reference. This time, I manually extracted the data for L=24 (triangle points).

5.6 Exporting the Data

Check the data points and save them in CSV format. The screen looks like this.

5.7 Verifying the Data

I compared the extracted data with the raw data. As shown in the figure below, the data was extracted with high accuracy.

6. Conclusion

“WebPlotDigitizer” is an excellent tool that can quickly and accurately extract data from graphs and plots. Its intuitive usability and multifunctionality make it highly useful for research and data analysis. I would like to continue using it actively in the future.

WebPlotDigitizer Official Website