基于YOLOv8的车载红外目标检测改进算法研究

doi:10.3969/j.issn.1000-1158.2025.02.03

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Abstract Aiming at the problem of mutual occlusion of targets and missed detection of small-scale targets in vehicle-mounted infrared image detection， an vehicle-mounted infrared target detection improved algorithm（VITD-YOLO） based on YOLOv8 is proposed. Firstly， a large-size feature network prediction layer（S-layer）， is added to the Neck network to enhance the detection accuracy of the network for small objects. Secondly， the C2F-DA module is designed in Backbone network， and the offset lightweight structure is used to enhance the perception ability of the model to the local features of the target. A dynamic convolutional head（Dy-head） detection module is designed by combining three different scales of self-attention to improve the location and classification accuracy of occluded and dense targets. Finally，Focal-SIoU is used as the loss function of the network to solve the problem of class imbalance of pedestrian and vehicle targets in the training samples and improve the training and reasoning ability of the network. The algorithm is tested on FLIR infrared data set. Experimental results show that VITD-YOLO has good detection effect and robustness and higher accuracy for small-scale target detection. The average precision of the algorithm reaches 91.2%，which is 2.5% higher than that of the original algorithm， and the recall rate reaches 83.4%， which is 3.2% higher than that of the original algorithm.

Key words： machine vision vehicle infrared target detection algorithm YOLOv8 assisted driving image recognition C2F-DA Focal-SioU

Received: 21 May 2024 Published: 04 March 2025

PACS:	TB96
	TP391.41

Fund:Research on auxiliary system of infrared target detection in night environment;Research on key technologies of intelligent detection and sorting of fruit quality based on machine vision

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	HOU Jun
	YANG Jie
	SHAO Kaiqing

Cite this article:

HOU Jun,YANG Jie,SHAO Kaiqing. Research on Vehicle Infrared Target Detection Improved Algorithm Based on YOLOv8[J]. Acta Metrologica Sinica, 2025, 46(2): 167-176.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2025.02.03 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2025/V46/I2/167

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