Bus Attendance System using Optical Character Recognition
P. Bhavani1, S. Vaishnavi2, P. Vennila3, V. Vijayalakshmi4
1P.Bhavani*, Assistant Professor, Department of Computer Science and Engineering, Sri Manakula Vinayagar Engineering College, Puducherry, India.
2S.Vaishnavi, Department of Computer Science and Engineering, Sri Manakula Vinayagar Engineering College, Puducherry, India.
3P.Vennila, Department of Computer Science and Engineering, Sri Manakula Vinayagar Engineering College, Puducherry, India.
4V.Vijayalakshmi, Department of Computer Science and Engineering, Sri Manakula Vinayagar Engineering College, Puducherry, India.
Manuscript received on March 30, 2020. | Revised Manuscript received on April 25, 2020. | Manuscript published on April 30, 2020. | PP: 2133-2136 | Volume-9 Issue-4, April 2020. | Retrieval Number: D7732049420/2020©BEIESP | DOI: 10.35940/ijeat.D7732.049420
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In today’s world managing the records of attendance of staffs, students, employee or bus is a tedious task. This project focuses on automating the bus attendance process through vehicle license plate recognition. As, the license plate is a feature that is peculiar to every vehicle, it would help in efficiently marking the bus attendance. The bus attendance system using RFID is a time consuming process. Hence we developed a project to efficiently mark attendance using number plate recognition and OCR. The system was trained using faster RCNN model with bus image dataset. The proposed system is the number plate is captured through surveillance camera and the captured image will be passed as an input to the neural network for training and the number plate will be detected. Character extraction is done using OCR and extracted character matched will be checked with the database and the attendance for particular bus will be marked.
Keywords: Bus attendance system, faster RCNN, Number plate detection, OCR.