A Novel Approach to Vehicle Number Identification using Raspberry pi 3
DOI:
https://doi.org//10.32628/CSEIT1952346Keywords:
Vehicle Number Identification, Raspberry pi 3, Open CV, OCR, GPIOAbstract
Vehicle Number Identification using Raspberry pi 3 is an image conversion technology which captures the license plate of a vehicle. The main aim is to make an effective and accurate license number plate identification system. This system is carried out and performed in the areas where traffic signals are present and the camera is placed on the signal which is connected to raspberry pi and it sends signals to the server and it can also be used in apartments or residencies for capturing all the vehicle numbers entering the building. This system at first detects the vehicle license plate and then captures it .It then converts the image into the text. The text of the license plate is displayed on the screen using the image conversion. Open CV and OCR are the two software’s used for image capturing and conversion of that into text format respectively. The resulting data is then displayed on the screen and saved into a folder. The whole system is developed on Raspberry Pi desktop and its performance is used in real-time. It is observed from this experiment that the system mainly detects and captures the vehicle license plate, converts the image into text and displays it on the screen successfully.
References
- Prof. Kumthekar A.V. , Ms. SayaliOwhal, Ms. SnehalSupekar, Ms. Bhagyashri Tupe4,” Recognition of vehicle number plate using Raspberry pi”,International Research Journal of Engineering and Technology (IRJET).
- D.Lavanya, C.V.Keerthilatha, Nirmala,”License Plate Extraction Of Images Using Raspberry Pi”,International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 4 Issue 1, January 2015.
- Bin Tian; Ye Li; Bo Li; Ding Wen, Rear-view vehicle detection and tracking by combining multiple parts for complex urban surveillance, in: IEEE Transactions on Intelligent Transportation Systems, vol.15, no.2, pp. 597–606 (April 2014).
- Ye Li; Bo Li; Bin Tian; Qingming Yao, Vehicle detection based on the and– or graph for congested traffic conditions, in: IEEE Transactions on Intelligent Transportation Systems, vol.14, no.2, pp.984–993 (June 2013).
- M. Anandhalli, V.P. Baligar, Improvised approach using background subtraction for vehicle detection, in: Advance Computing Conference (IACC), 2015 IEEE International, pp. 303–308, 12–13 (June 2015.
- Renjun Lin, Xianbin Cao, Yanwu Xu, Changxia Wu, Hong Qiao, Air-borne moving vehicle detection for video surveillance of urban traffic, in: Intelligent Vehicles Symposium, 2009 IEEE, pp. 203–208 (3–5 June 2009).
- Zezhong Zheng; Guoqing Zhou; Yong Wang; Yalan Liu; Xiaowen Li; Xiaoting Wang; Ling Jiang, A novel vehicle detection method with high resolution highway aerial image, in: IEEE Journal of Selected ToPics in Applied Earth Observations and Remote Sensing, vol. 6, no. 6, pp. 2338– 2343 (Dec. 2013
Downloads
Published
Issue
Section
License
Copyright (c) IJSRCSEIT
This work is licensed under a Creative Commons Attribution 4.0 International License.