Feature enhancement based detection of traffic signs in foggy environment

Ruotong Wei; Jinzhao Zhang; Xiao Wang; Ruihong Zou

doi:10.1117/12.3005796

10 October 2023 Feature enhancement based detection of traffic signs in foggy environment

Ruotong Wei, Jinzhao Zhang, Xiao Wang, Ruihong Zou

Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 127995J (2023) https://doi.org/10.1117/12.3005796
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia

Abstract

Aiming at the problem of missing detection and low accuracy of traffic signs in a foggy environment, the original YOLOv5 target detection algorithm was improved. First, to reduce the loss of traffic signs in the Foggy image in the process of deep convolution network transmission, replace the Backbone end convolution with the Transformer module, established the YOLOv5-Transformer model; Secondly, to enrich the semantic information in the shallow network, by joining the Path Aggregation Networks (PAN) to achieve semantic information fusion with the deep network; Further, the YOLOv5- 4detect model is proposed, which added small size detection head to the original YOLOv5 network model to detect the fused feature maps . The results showed that the YOLOv5-Transformer model and YOLOv5-4 detect model have improved the testing performance of traffic signs by 5.5% and 9.3% in sunny environment; The detection results of traffic signs in foggy environment increased by 9.4% and 15.8%. The experiments illustrate that it is more effective in foggy environments by adding fusion channels than introducing a self-attention mechanism via Transformer. YOLOv5-4detect can significantly improve the performance of YOLOv5 in traffic signs detection.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ruotong Wei, Jinzhao Zhang, Xiao Wang, and Ruihong Zou "Feature enhancement based detection of traffic signs in foggy environment", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 127995J (10 October 2023); https://doi.org/10.1117/12.3005796

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KEYWORDS

Feature extraction

Environmental sensing

Detection and tracking algorithms

Transformers

Target detection

Head

Education and training

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