铁路周界防护是保障铁路运输安全的关键,而视频监控是铁路周界防护中应用最为广泛的技术手段.针对视频监控在夜间或恶劣光线条件下存在误报率及漏报率大的问题,考虑到红外通过物体热辐射成像,具有抗光线变化和恶劣天气干扰的能力,本文研究了红外与可见光图像结合实现全天候周界入侵检测的问题.首先在分析铁路周界防护技术现状的基础上,讨论了红外与可见光图像融合目标检测技术的研究重点与难点;然后分别介绍了图像配准和目标检测的一般方法及流程,分析了红外与可见光图像配准、红外目标检测、红外与可见光图像融合目标检测的研究进展以及铁路场景下的相关研究现状;最后展望了铁路周界防护应用场景下多源图像目标检测技术的发展趋势,红外与可见光视频图像结合既能实现全天候有效入侵检测,又能保证入侵目标可视化效果,便于后续智能分析.
Railway perimeter protection is crucial for ensuring the safety of railway transportation,and video surveillance stands out as the most widely utilized technology in this domain.Aiming to address the issue of high false positive and false negative rates under challenging lighting conditions,particu-larly at night,given the ability of infrared imaging to capture thermal radiation from objects and its re-silience against variations in lighting and adverse weather,this study investigates the integration of in-frared and visible light images to enable all-weather perimeter intrusion detection.Firstly,based on an analysis of the current state of railway perimeter protection technology,the paper discusses the focal points and challenges in research related to object detection through the fusion of infrared and visible light images.Subsequently,it outlines the general methods and procedures for image registration and object detection,while analyzing the progress made in infrared image registration,infrared target de-tection,and the research advancements in fusion-based object detection using infrared and visible light images in railway scenarios.Finally,this paper provides an outlook on the future trends in multi-source image object detection technology within the context of railway perimeter protection applica-tions.The combination of infrared and visible light video images not only facilitates effective intrusion detection under all-weather conditions but also ensures the visual representation of intrusion targets,thereby facilitating subsequent intelligent analysis.