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Home / Archives / Volume-5 / Issue-4 / Article-2

Volume - 5 | Issue - 4 | december 2023

CNN based System for Automatic Number Plate Recognition Open Access
Gobinda Pandey  , Karun K C, Nirajan Lamichhane, Utsav Subedi  129
Pages: 347-364
Cite this article
Pandey, Gobinda, Karun K C, Nirajan Lamichhane, and Utsav Subedi. "CNN based System for Automatic Number Plate Recognition." Journal of Soft Computing Paradigm 5, no. 4 (2023): 347-364
Published
09 January, 2024
Abstract

This study presents a comprehensive approach to Automated Vehicle Number Plate Detection and Recognition, employing image processing and Convolutional Neural Networks (CNNs). The system encompasses two main stages: number plate detection and recognition. Utilizing a digital camera, the system employs image processing to segment the number plate region accurately. A super-resolution method is then applied via CNNs to enhance the image quality. Subsequently, a bounding box method isolates individual characters for precise recognition. In the recognition phase, CNNs extract features for effective classification. The study aims to advance automated vehicle identification systems for law enforcement and parking management applications, promising accurate and efficient number plate detection and recognition. The proposed work has also developed a user interface to ensure the successfulness of the objectives aimed.

Keywords

Number Plate Detection Number Plate Recognition Image Processing Convolutional Neural Networks (CNNs) Digital Camera Bounding Box Method Character Segmentation.

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