Please use this identifier to cite or link to this item:
|Title:||Car license plate recognition using deep learning||Authors:||Tan, Jason Jit Hao||Keywords:||Engineering::Electrical and electronic engineering||Issue Date:||2022||Publisher:||Nanyang Technological University||Source:||Tan, J. J. H. (2022). Car license plate recognition using deep learning. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157158||Abstract:||Emerging technologies towards smart vehicles and Intelligent Transportation System (ITS) have revolutionized many aspects of human life. One of the most important applications of the ITS includes Video Surveillance which is commonly used everywhere. By pairing it with Artificial Intelligence (AI), it may be enhanced and further developed into useful applications such as License Plate Recognition. Currently, there are insufficient license plate recognition systems that can be used to identify the car license plates of Singapore. Furthermore, there is a lack of publicly available datasets of Singapore car license plates. This study aims to explore and develop a model using deep learning methods to identify the characters of Singapore car license plates. With the focus on being lightweight and having fast performance, while maintaining sufficient accuracy for functional use. LPRNet fulfils this requirement by implementing a lightweight model which works without preliminary character segmentation. However, it will be compared with other engines such as Tesseract Optical Character Recognition (OCR) to distinguish the differences in speed and performance.||URI:||https://hdl.handle.net/10356/157158||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Student Reports (FYP/IA/PA/PI)|
Updated on May 20, 2022
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.