In the current era of automation, vehicle automation plays a vital role in the current technological evolution. Vehicle automation and detection mechanisms are attracting so many research enthusiasts in this period. This research work has utilized this opportunity to play our role by creating our project for Surveillance-Based Spotting and Categorization of Automobiles. The main focus of our project lies in the detection and categorization of vehicles that are in motion and in still positions. Though there are numerous methods of vehicle detection using sensors, microchips, and many other technologies, all of these tend to be vulnerable to environmental factors that affect their longevity and increase the cost of their implementation as well as their maintenance. To avoid these additional costs, a computer vision technology that uses a vision-based detection mechanism is used to detect the vehicles from the real-time video input with the help of image fragmentation and pattern recognition. The goal of this project is to provide a feasible and cost-effective system to spot and categorize various kinds of automobiles using OpenCV and YOLOv3.


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    Title :

    Surveillance Based Spotting and Categorization of Automobiles


    Contributors:


    Publication date :

    2022-05-25


    Size :

    2093276 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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