A Broad Survey on Performance Analysis of Number Plate Recognition from Stationary Images and Video Sequences
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2018-07-15 https://doi.org/10.14419/ijet.v7i3.10.15652
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Image Processing, Multilayer Perceptron, Neural Network, Performance Analysis, Optical Character Recognition (OCR) -
Abstract
Licensed Number plate recognition plays vital role in smart cities for maintaining Law & Order and traffic management. NPR based system mainly involves four stages namely 1) Image capture & Pre-Processing 2) Number plate area determination 3) Character Segmentations 4) Recognition of all character. This survey paper extensively analyzed the method of extraction of number plate, its platform, performance and execution time. With the development of Multilayer Perceptron Network accuracy and time in image processing has been achieved up to a great instant. Hence this analysis will help the precise assessment in establishing research and enable developers to assess which strategies are aggressive in present environment.
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How to Cite
Khan, T., J S Yadav, D., & Dheeraj Agarwal, D. (2018). A Broad Survey on Performance Analysis of Number Plate Recognition from Stationary Images and Video Sequences. International Journal of Engineering & Technology, 7(3.10), 164-168. https://doi.org/10.14419/ijet.v7i3.10.15652Received date: 2018-07-14
Accepted date: 2018-07-14
Published date: 2018-07-15