SuroTex:周围纹理数据集
Muhammad Ardi Putra1, Wahyono1, Agus Harjoko1
1Department of Computer Science and Electronics, Universitas Gadjah Mada, Indonesia.
Data in brief
|February 10, 2025
概括
一个新的数据集,SuroTex,解决了现有的纹理分类数据集的局限性. 它在50个类别中提供5000张图像,尺寸均,提高了纹理分析的可靠性.
科学领域:
- 计算机视觉 计算机视觉
- 图像处理 图像处理
背景情况:
- 现有的纹理数据集有局限性,包括有限数量的类和不统一的图像大小.
- 这些局限性影响了纹理分类算法和分析的可靠性.
- 这就需要开发更全面和标准化的纹理数据集.
研究的目的:
- 介绍SuroTex (周围纹理) 数据集,以克服当前纹理数据集的缺陷.
- 为一般和特定的纹理分类任务提供基准数据集.
- 促进开发更强大的纹理分析模型.
主要方法:
- 在2023年11月,在韩国乌尔山收集了5000个RGB图像纹理.
- 将数据集组织成50个不同的纹理类,每个类有100个样本.
- 确保所有图像均大小为400 × 400像素.
主要成果:
- SuroTex数据集包括5000个高分辨率 (400×400像素) 的纹理图像.
- 数据集被分为50个类别,为分类任务提供了更广泛的范围.
- 统一的图像大小提高了纹理分析的一致性.
结论:
- SuroTex为推进纹理分类和一般图像分类研究提供了宝贵的资源.
- 数据集可以作为评估新算法和开发预训练模型的基准.
- 在SuroTex上训练的模型可以为材料分类等专业应用进行微调.
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