Security and Surveillance System Using OpenCV
Authors
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Department of Electronics and Communication Engineering, Greater Noida Institute of Technology, Gautam Buddh Nagar, Greater Noida, Uttar Pradesh 201306 ,IN
Shiv Narain Gupta -
Department of Electronics and Communication Engineering, GL Bajaj Institute of Technology & Management, Greater Noida ,INVivek Gupta
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Department of Electronics and Communication Engineering, Greater Noida Institute of Technology, Gautam Buddh Nagar, Greater Noida, Uttar Pradesh 201306 ,INArpit Kumar
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Department of Electronics and Communication Engineering, Greater Noida Institute of Technology, Gautam Buddh Nagar, Greater Noida, Uttar Pradesh 201306 ,INUmang Singh
DOI:
https://doi.org/10.18311/jmmf/2023/33928Keywords:
Moving Object Tracking, Artificial Learning, Tracking Technology, Image Processing, OpenCV Module.Abstract
Detection and recognizing the moving objects is needed in terms of learning direction, as a classification algorithm, it employs OpenCV and to create an integrated multi-module system, uses the Qt interface library. A software platform for achieving a moving object with a single objective detection and identification. In a picture, an item tracking system is used to monitor the motion trajectory of an object. First, we use OpenCV’s pick ROI function to choose an item on a frame and utilise the built-in tracker to monitor its movements. we utilize YOLO to identify and track objects in each frame using object centrefold and size comparison. Then, by identifying the item in the first frame using YOLO and tracking it with select ROI, we integrate YOLO detection with OpenCV’s built-in tracker. Video tracking is widely utilized in a variety of applications, including human-computer interaction, for surveillance, traffic control, and medical imaging.
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
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