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用于探测埋藏地雷的热成像图像数据集。

Dataset of thermographic images for the detection of buried landmines.

作者信息

Tenorio-Tamayo Hermes Alejandro, Forero-Ramírez Juan Camilo, García Bryan, Loaiza-Correa Humberto, Restrepo-Girón Andrés David, Nope-Rodríguez Sandra Esperanza, Barandica-López Asfur, Buitrago-Molina José Tomás

机构信息

Escuela de Ingeniería Eléctrica y Electrónica (EIEE), Facultad de Ingeniería, Universidad del Valle, Colombia.

出版信息

Data Brief. 2023 Jul 24;49:109443. doi: 10.1016/j.dib.2023.109443. eCollection 2023 Aug.

Abstract

This article presents a dataset of thermographic images of terrain with antipersonnel mines to identify the presence or absence of these artifacts using machine learning and artificial vision techniques. The dataset has 2700 thermographic images acquired at different heights, using a Zenmuse XT infrared camera (7-13 µm), embedded in the DJI Matrice 100 drone. The data acquisition experiment consists of capturing aerial infrared images of a terrain where elements with characteristics similar to antipersonnel mines type legbreaker were buried. The mines were planted in the ground between 0 cm and 10 cm deep and were spread over an area of 10 m x 10 m. The drone used a flight protocol that set the trajectory, the time of the flight, the acquisition height, and the image sampling frequency. This dataset was used in "Detection of "legbreaker" antipersonnel landmines by analysis of aerial thermographic images of the soil" [7].

摘要

本文展示了一个带有杀伤人员地雷的地形热成像图像数据集,旨在使用机器学习和人工视觉技术识别这些物体的存在与否。该数据集包含2700张热成像图像,这些图像是使用嵌入在大疆经纬M100无人机中的禅思XT红外相机(7 - 13微米)在不同高度获取的。数据采集实验包括拍摄一片埋有与“碎腿器”型杀伤人员地雷特征相似的物体的地形的空中红外图像。地雷埋在地下0厘米至10厘米深处,分布在10米×10米的区域内。无人机采用了设定轨迹、飞行时间、采集高度和图像采样频率的飞行协议。这个数据集被用于“通过分析土壤的空中热成像图像检测‘碎腿器’杀伤人员地雷”[7]。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e47c/10403701/bc82a407f9b2/gr1.jpg

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