CrackAirport: A dataset for segmentation for airport pavements in General Aviation

CrackAirport features images containing unique elements such as aircraft, T-hangars, vegetation, airport markings and signs, as well as evidence of previous maintenance. The dataset was captured using a Sony ILCE-7RM4A camera mounted on a drone flying at an altitude of 100 feet AGL. The imagery was sourced from various local airports in Tennessee and includes common pavement distresses and environmental patterns typical of airport surfaces. The images were annotated and then cropped into 512x512 pixel segments for training. To ensure a balanced ratio of crack pixels to background pixels, approximately 2,000 representative images were selected, specifically excluding those with minimal crack presence.

CrackAirport数据集包含涵盖多种独特元素的图像，这些元素包括航空器、T型机库（T-hangars）、植被、机场标识与标牌，以及既往维护痕迹。该数据集由搭载于无人机的索尼ILCE-7RM4A相机拍摄，无人机飞行高度为100英尺离地高度（AGL）。图像数据取自田纳西州的多处本地机场，涵盖机场道面常见的铺装病害与典型环境特征。所有图像均经过标注，随后被裁剪为512×512像素的图像块用于模型训练。为保证裂纹像素与背景像素的比例均衡，数据集筛选了约2000张具有代表性的图像，特别排除了裂纹占比极低的样本。

搜集汇总

背景与挑战

背景概述

CrackAirport是一个用于通用航空机场路面分割的数据集，包含从田纳西州多个机场采集的图像，涵盖飞机、T型机库、植被、机场标记和先前维护痕迹等独特元素。数据集通过无人机在100英尺高度拍摄，图像经过标注并裁剪为512x512像素片段，精选约2000张代表性图像以确保裂纹像素与背景的平衡，适用于机场路面病害检测和分割任务。