An Implementable System for Detection and Identification of License Plates in Pakistan

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Date
2020
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UMT, Lahore
Abstract
Automated License Plate Identification (ANPR) is a large-scale monitoring system that Photographs vehicles and recognizes their license numbers. The ANPR can help Detect stolen vehicles. Stolen vehicles can be traced effectively. This research provides a way to recognize the use of the ANPR system in highways. Using different vehicles, a rear- view image of the vehicle is captured and processed Algorithm. In this context, the license plate area is located using a new function how to detect license plates that contain multiple algorithms. Whose vehicle plate image is captured by cameras and processed to capture the image License plate information. This system is implemented not only to reduce human consumption but also to facilitate human labor because of the power and its potential use of development of automatic license plate. The identification system will result in greater efficiency in the vehicle monitoring system and number plate Identification systems are used commercially, abroad and locally. This is the system Implemented using the Python Image Processing Toolbox, which uses optical characters Image identification for reading vehicle license plates. The data is collected from safe city and collect by myself locally, where data in the imagery structure is presented. A corresponding model is developed for the purpose of identification and recognition of License Plates and attain a recognition accuracy of at least 95 percent. Significant computing power is required in the case of License Plate Recognition to achieve a satisfactory proficient of recognition in a neural network. This research is a step towards smart city plan of Pakistan. In today's world where basic electronics find their place in areas like home automation, automotive automation. Automatic water storage system and so on, it will take us a little further in the smart city plan.
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