Powerline Image Dataset (Infrared-IR and Visible Light-VL)

Despite a relatively crowded literature about detection of power lines for aircraft safety, the works are mostly optimized with very few training images; some even use artificially generated images. The IR imaging case is even less utilized. The reason is clearly the tremendous workload to obtain real images. With this demand in mind, the authors cooperated with the Turkish Electricity Transmission Company (TEIAS) to obtain video captures from actual aircrafts. Later, the authors made a thorough inspection over the video frames to isolate, capture and clean thousands of valuable images. In this content, 4000 IR and 4000 VL images are acquired and scaled to a size of 128x128. The IR folder contains 2000 IR images with power line and 2000 IR images with no power line. The VL folder contains 2000 VL images with power line and 2000 VL images with no power line. The IR and VL groups were deliberately constructed to contain both regular and especially confusing scenes. "TY" shows that there are no power lines in the images. "TV" shows that there are power lines in the images. The videos were captured from 21 different regions all over Turkey at different seasonal days. Due to varying background behavior, varying temperatures and weather conditions, and varying lighting conditions, the achieved positive set contains several difficult scenes where low contrast causes close-to invisibility for power lines. The original video resolutions were 576x325 for IR and full HD for VL, however, the captured frames were scaled down to smaller sizes and the effect of resizing was tested for various image sizes. An image size of 128x128 is sufficient for a consistently accurate power line recognition.

尽管当前针对飞行器安全的电力线检测相关研究文献已较为丰富，但绝大多数现有工作仅依靠极少量训练图像进行优化，部分研究甚至仅使用人工生成的图像开展实验。而红外成像（IR）的相关应用案例则更为匮乏，其核心原因在于获取真实红外图像的工作量极其繁重。为此，研究团队与土耳其输电公司（Turkish Electricity Transmission Company, TEIAS）合作，获取了实际飞行器搭载采集的视频片段。随后，团队对视频帧进行了全面筛选，从中提取并清洗出数千张高价值图像。最终共获取4000张红外成像（IR）图像与4000张可见光成像（Visible Light, VL）图像，并将所有图像统一缩放至128×128像素尺寸。红外成像数据集文件夹中包含2000张含电力线的红外图像与2000张不含电力线的红外图像；可见光成像数据集文件夹中则包含2000张含电力线的可见光图像与2000张不含电力线的可见光图像。红外与可见光数据集均刻意兼顾了常规场景与极具干扰性的复杂场景。其中标签"TY"代表图像中无电力线，"TV"代表图像中存在电力线。所有视频均采集自土耳其境内21个不同区域，且拍摄时间覆盖了不同季节。由于拍摄时背景环境、气温、天气状况与光照条件均存在差异，正样本集中包含了大量高难度场景：部分场景中电力线与背景对比度极低，几乎难以辨识。原始视频的分辨率分别为：红外视频576×325像素，可见光视频为全高清分辨率。研究团队将采集到的视频帧统一缩放至更小尺寸，并针对多种图像尺寸的缩放效果进行了测试，最终确定128×128像素尺寸足以实现稳定且准确的电力线识别。

搜集汇总

背景与挑战

背景概述

Powerline Image Dataset是一个包含8000张红外和可见光图像的数据集，专门用于电力线检测研究，图像尺寸为128x128，涵盖了多种复杂场景和条件，适合用于计算机视觉和机器学习任务。