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@article{144325,
        author = {KISHOR KUMAR SR and IYYAPPAN M and SAMPATH R},
        title = {VEHICLE DETECTION, CLASSIFICATION AND COUNTING (VDCC)},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {3},
        number = {10},
        pages = {136-138},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=144325},
        abstract = {Vehicle detection, classification and counting are very important for civilian and government applications, such as highway monitoring, traffic planning, toll collection and traffic flow. Automatic detecting and counting vehicles in CCTV video on highways is a very challenging problem in computer vision with important practical applications such as to monitor activities at traffic intersections for detecting congestions, and then predict the traffic flow in regulating traffic. Manually reviewing the large amount of data they generate is often impractical. The background subtraction based on morphological transformation for tracking and counting vehicles on highways is proposed. Proposed algorithm segments the image by preserving important edges which improves the adaptive background mixture model and makes the system learn faster. This project use SVM technique for Classification of vehicles. With the help of Morphological Operations along with SVM unwanted noise and holes in the video frame is removed. Finally, Mathematical operation is used for the counting of vehicles to generate the report on vehicle flow.},
        keywords = {SVM, ITS, Background Subtraction, Morphological Operations, Segmentation},
        month = {},
        }