Automatic number plate detection and un-manned challan generation for the odd/even rules in Delhi. (2021)

• Record Type: Journal Article
• Authors: Arora, Ashima; Saluja, Deepak; Parmar, Nitesh; Goyal, Deepam; Senthil, V.
• Is Part Of: Materials today. Volume 43:Part 1(2021)
• Page Start: 231
• Page End: 236
• Publication Date: 2021
• Subjects: Automatic license plate recognition (ALPR) -- Optical character recognition (OCR) -- Odd/even transport rule -- Character recognition -- Image acquisition and processing; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2020.11.650
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: This article addresses automatic license plate recognizer as a key element of today's fast trending approaches used for smart city development. The deployment of heavy manual forces is the biggest challenge in the path of efficient execution of transportation rules in metro cities. In order to help the government in achieving this milestone, a thorough research helped in developing a product which could very effectively and efficiently be used in the implementation of odd/even transport rule coined by the NCT Government, Delhi. Automatic license plate recognition has become the latest trend in the management of contemporary urban and national street arrangements, and this latest trend has been blended with programming in python to enable a handy product for the government to easily enable them to distinguish between the faulty and genuine vehicles without much need of manual forces. This article throws light on the techniques used for making this product and the literature survey done on the previously existing techniques.