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LI B , WANG B , HAN J Y , et al . Infrared image moving object detection technology based on onboard computer [J ] . Acta Armamentarii , 2022 , 43 ( S1 ): 66 - 73 . (in Chinese) DOI: 10.12382/bgxb.2022.A012 http://doi.org/10.12382/bgxb.2022.A012 As an important part of driverless vehicle platform，the environmental perception system is the basis and premise to realize as the path planning and decision control function. Based on the onboard computer，an infrared image moving object detection system in complex scenes is designed.The browser/server architecture is used in the detection system. After the client browser requests for services，the server applies the improved YOLOv2 algorithm to detect the infrared images transmitted by the onboard RapidIO high-speed bus in real time.the missed detection and error detection rates are effectively reduced by dimensional re-clustering and improved activation function.In order to make up for disadvantages of low contrast and weak texture features of infrared images，bilateral filtering image enhancement algorithm based on histogram equalization is proposed，which can effectively maintain the image contour details.The results show that the real-time detection accuracy of the improved YOLOv2 is increased by 4.1% compared with the original algrithm and the image preprocessing significantly improves the detection accuracy.

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