The rapid growth in global traffic and population has intensified challenges such as air pollution, road congestion, and accident rates, highlighting the need for intelligent transportation management systems equipped with automated traffic monitoring. This paper introduces a deep learning-based smart traffic surveillance system that addresses these challenges by performing key tasks of vehicle detection, classification, and tracking. The system preprocesses traffic images using Total Variation Denoising (TVD) for dynamic contrast adjustment, followed by segmentation via Entropy Rate Superpixel Segmentation (ERS) to cluster uniform regions and reduce image complexity. YOLOv9 is employed for vehicle detection, with subsequent modules handling classification and tracking. Feature extraction for classification utilizes Gray-Level Co-occurrence Matrix (GLCM) and Zernike Moments, while NASNet serves as the classifier. Vehicle counting is achieved through the Voronoi Tessellation algorithm, which uses appearance and motion features to track vehicles across frames, complemented by Farneback Optical Flow for tracking. Evaluated on the UAVDT and UAVID datasets, the system outperforms state-of-the-art methods, achieving detection precision of 0.914 and 0.932, tracking precision of 0.887 and 0.905, and classification accuracy of 91.60% and 92.80%, respectively, demonstrating its effectiveness in automated traffic monitoring.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Intelligent Transportation Surveillance via YOLOv9 and NASNet over Aerial Imagery


    Beteiligte:
    Hanzla, Muhammad (Autor:in) / Jalal, Ahmad (Autor:in)


    Erscheinungsdatum :

    18.02.2025


    Format / Umfang :

    1031386 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





    Driver Drowsiness Detection Using NasNet Mobile, MobileNetV2, and EfficientNetB0

    Wunan, Thomas Dante / Jappy, Pretty Calista / Aurelia, Stephanie et al. | IEEE | 2024


    Automatic License Plate Detection Using YOLOv9

    V, Nivethitha / Rajan, Shruthika / Sriram, Suthir et al. | IEEE | 2024


    Real-Time Traffic Sign Recognition for Smart Transportation in Indian Urban Environments Using YOLOv9

    Kumaran, N. Nithish / William, J.S. Joewin / Gnaneswar, K. et al. | IEEE | 2025