An Optimized Algorithm for Car Plate Recognition using Artificial Neural Network for a Mobile Application without Segmentation

N. Sakthivel, D. Swamydoss


The main objective of this paper, to create a mobile application without segmentation using Intelligent Transport system. Today’s we are living in the mobile world, anywhere and anytime with mobile application which is used mainly in transport mode especially in navigation. User can monitor their lane of transport, traffic and also many applications which make the user more safety and security. In paper, to develop , a simple algorithm is presented for Car Plate Recognition (CPR) system based on Artificial Neural Network. This is simulated mobile application without segmentation. This proposed optimized algorithm is a mainly categorized into four major parts: Plate Extraction, Digitalization, Character Recognition and Optimization. Plate Extraction is to extract the appropriate region, convert the given images into binary value in digitalization, Character recognition are performed from the weight matrix and optimization has been done to retrieve the exact data to mobile application. This new approach provides new trends in mobile application for CPR.


Intelligent Transport System (ITS), Car Plate Recognition (CPR), Artificial Neural Network (ANN)

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