Opto-Electronic Engineering, Volume. 51, Issue 6, 240055-1(2024)

A traffic sign recognition method based on improved YOLOv5

Liguo Qu1,2、*, Xin Zhang1, Zibao Lu1, Yuling Liu1, and Guohao Chen3
Author Affiliations
  • 1School of Physics and Electronic Information, Anhui Normal University, Wuhu, Anhui 241002, China
  • 2Anhui Provincial Engineering Research Center for Information Fusion and Control of Intelligent Robots, Wuhu, Anhui 241002, China
  • 3Wuhan Mingke Rail Transit Equipment Co., Ltd., Wuhan, Hubei 430074, China
  • show less
    References(30)

    [1] Wang R X, Wu J P, Xu H. Overview of research and application on autonomous vehicle oriented perception system simulation[J]. J Syst Simul, 34, 2507-2521(2022).

    [2] Acharya S, Nanda P K. Adjacent LBP and LTP based background modeling with mixed-mode learning for foreground detection[J]. Pattern Anal Appl, 24, 1047-1074(2021).

    [3] Shao F M, Wang X Q, Meng F J et al. Real-time traffic sign detection and recognition method based on simplified Gabor wavelets and CNNs[J]. Sensors, 18, 3192(2018).

    [4] Maria Dominic Savio M, Deepa T, Bonasu A et al. Image processing for face recognition using HAAR, HOG, and SVM algorithms[J]. J Phys Conf Ser, 1964, 062023(2021).

    [5] Burges C J C. A tutorial on support vector machines for pattern recognition[J]. Data Min Knowl Discovery, 2, 121-167(1998).

    [6] Thamilselvan P. Lung cancer prediction and classification using adaboost data mining algorithm[J]. Int J Comput Theory Eng, 14, 149-154(2022).

    [9] Ren S Q, He K M, Girshick R et al. Faster R-CNN: towards real-time object detection with region proposal networks[J]. IEEE Trans Pattern Anal Mach Intell, 39, 1137-1149(2017).

    [17] Chen X, Peng D L, Gu Y. Real-time object detection for UAV images based on improved YOLOv5s[J]. Opto-Electron Eng, 49, 210372(2022).

    [18] Yang J, Sun T, Zhu W C et al. A lightweight traffic sign recognition model based on improved YOLOv5[J]. IEEE Access, 11, 115998-116010(2023).

    [19] Chen L, Zhang J L, Peng H et al. Few-shot image classification via multi-scale attention and domain adaptation[J]. Opto-Electron Eng, 50, 220232(2023).

    [20] Zhang J M, Xie Z P, Sun J et al. A cascaded R-CNN with multiscale attention and imbalanced samples for traffic sign detection[J]. IEEE Access, 8, 29742-29754(2020).

    [21] Zhang H B, Qin L F, Li J et al. Real-time detection method for small traffic signs based on Yolov3[J]. IEEE Access, 8, 64145-64156(2020).

    [22] Guo Y, Liang R L, Wang R M. Cross-domain adaptive object detection based on CNN image enhancement in foggy conditions[J]. Comput Eng Appl, 59, 187-195(2023).

    [24] Wang Y D, Guo J C, Wang T B. Algorithm for foggy-image pedestrian and vehicle detection[J]. J Xidian Univ, 47, 70-77(2020).

    [25] Lang B K, Lü B, Wu J Q et al. A traffic sign detection model based on coordinate attention-bidirectional feature pyramid network[J]. J Shenzhen Univ (Sci Eng), 40, 335-343(2023).

    [26] Zhu H Y, Han J N, Xu Y. Printed circuit board blemishes detection based on the improved YOLOv5s[J]. Foreign Electron Meas Technol, 42, 152-159(2023).

    [27] Wang Y W, Lu Y, Dou Y H et al. Synchronous GPS spoofing Identification based on K-means clustering[J]. J Electron Inf Technol, 45, 4137-4149(2023).

    [28] Zhang Z D, Tan M L, Lan Z C et al. CDNet: a real-time and robust crosswalk detection network on Jetson nano based on YOLOv5[J]. Neural Comput Appl, 34, 10719-10730(2022).

    [30] Lin T Y, Goyal P, Girshick R et al. Focal loss for dense object detection[J]. IEEE Trans Pattern Anal Mach Intell, 42, 318-327(2020).

    Tools

    Get Citation

    Copy Citation Text

    Liguo Qu, Xin Zhang, Zibao Lu, Yuling Liu, Guohao Chen. A traffic sign recognition method based on improved YOLOv5[J]. Opto-Electronic Engineering, 2024, 51(6): 240055-1

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category:

    Received: Mar. 7, 2024

    Accepted: Jun. 4, 2024

    Published Online: Oct. 21, 2024

    The Author Email: Liguo Qu (曲立国)

    DOI:10.12086/oee.2024.240055

    Topics