Wind Turbine Blade Surfaces Dataset

The proposed dataset aims to provide a number of wind turbine blade images for testing and training purposes. The featured datasets can be used for testing and evaluation of Structure from Motion algorithms for 3D reconstruction, as data for machine learning algorithms for detecting damaged areas on blades or for quantifying blade surface roughness. Images are taken using Canon 5Ds DSLR camera with resolution of 8688 x 5792. The images come with EXIF data, containing additional information about the used capturing settings.

The dataset is separated into two parts:
- A dataset containing 5 wind turbine blade patches of areas of different surface structure. Two of the patches are of damaged areas, two of the patches are of rough areas, without pronounced surface deformations and one of the patches is a reference area, that does not contain any roughness or damages. The final patch contains the whole of the blade's edge area and is comprised of a mix of severely damaged areas, areas of small roughness and clear areas. The dataset also contains ground truth microscopy data for two of the damaged patches. The ground truth is scaled to absolute scale.

- A dataset containing images of a small blade segment. The blade has been sand blasted, to imitate prolonged real world use. The images are taken both outdoor and indoor. The indoor images contain patches specifying areas of interest - one containing a rough patch and one containing damages. The outdoor images are focused on the whole blade and do not contain patches. The dataset also contains ground truth microscopy data for the two patches, which is scaled to absolute scale.

本提议的数据集旨在提供一系列风力涡轮机叶片图像，以供测试和训练之用。所收录的精选数据集可用于检验和评估结构从运动算法的3D重建性能，亦可作为机器学习算法识别叶片损坏区域或量化叶片表面粗糙度的数据。图像采用佳能5Ds单镜头反光相机拍摄，分辨率为8688 x 5792。图像附带EXIF数据，其中包含有关拍摄设置等附加信息。

数据集分为两部分：
- 第一部分包含5个不同表面结构区域的风力涡轮机叶片区域图像。其中两个区域为损坏区域，两个区域为粗糙区域，表面无明显变形，一个区域为参考区域，不含任何粗糙度或损坏。最后一个区域包含叶片边缘的全区域，由严重损坏区域、轻微粗糙区域和清晰区域混合组成。数据集还包含两个损坏区域的地面真实显微镜数据，已缩放至绝对比例。
- 第二部分包含小型叶片段图像。叶片经过喷砂处理，以模拟长时间的实际使用情况。图像在室内外均进行了拍摄。室内图像包含指定感兴趣区域的补丁 - 一个包含粗糙区域，另一个包含损坏区域。室外图像专注于整个叶片，不包含补丁。数据集还包含两个补丁的地面真实显微镜数据，已缩放至绝对比例。

搜集汇总

背景与挑战

背景概述

该数据集提供风力涡轮机叶片表面图像，用于3D重建和机器学习应用，包含损伤、粗糙和参考区域的图像及地面真实数据。数据集分为两部分，分别针对不同叶片区域和状态，图像分辨率高且附带EXIF信息。