International Research Journal of Engineering and Technology (IRJET) Volume: 11 Issue: 04 | Apr 2024
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e-ISSN: 2395-0056 p-ISSN: 2395-0072
Moving Vehicle Registration Plate Detection System Using OCR Sanket S. Tabhane1 , Swapnali G. Sapkal2, Isha R. Sinkar3, Yash N. Zagade5 , Tejas J. Sonkusare4, Yash N. Zagade5 , Dr.Anuja A. Khodaskar6 12345Students of Final year, Department of Computer Science & Engineering, Sipna College of Engineering and
Technology, Amravati, Maharashtra, India 6 Assistant Professor, Department of Computer Science & Engineering, Sipna College of Engineering and Technology,
Amravati, Maharashtra, India -------------------------------------------------------------------------***-----------------------------------------------------------------------Additionally, the paper discusses the integration of machine Abstract - The system titled “Moving Vehicle Registration
learning models, security measures, and optimization techniques for resource efficiency. The proposed system architecture aims to achieve real-time performance, to dynamic environmental conditions, and robust security measures.
Plate Detection System Using OCR presents a comprehensive study on the development of an automatic license plate recognition system for moving vehicles. Through the integration of sophisticated image processing techniques, optical character recognition (OCR) technologies, and machine learning models, the project seeks to address the difficulties involved in real-time vehicle plate identification and recognition. The proposed system architecture involves the use of morphological operations for character extraction, noise reduction, and character segmentation, followed by OCR for character recognition. Additionally, it highlights the challenges related to dynamic environmental conditions and real-time processing requirements in the context of moving vehicle number plate registration. The system aims to contribute to the advancement of intelligent transportation system and vehicular access control through efficient and accurate license plate recognition.
1.1 Objectives of the paper Developing a Moving Vehicle Registration Plate Detection System using OCR technology. Integrating advanced image processing algorithms and machine learning models for efficient license plate recognition. Addressing challenges related to real-time vehicle plate detection and recognition. Implementing morphological operations for character extraction, noise reduction, and character segmentation. Enhancing the system's efficiency and accuracy in recognizing license plates under dynamic environmental conditions. Contributing to the advancement of intelligent transportation systems and vehicular access control through innovative license Plate recognition techniques.
Key Words: – OCR, Character extraction, Noise reduction, Real-time processing
1. INTRODUCTION The development of a Moving Vehicle Registration Plate Detection System using Optical Character recognition is a critical area of research in the field of computer science and engineering. This system aims to address the growing need for efficient and accurate license plate recognition in various application, including traffic monitoring, automatic toll payment, and parking lot access control. The integration of OCR technology and advanced algorithms presents a promising solution to the challenges posed by dynamic environmental conditions, high-speed vehicle movement, and diverse license plate design. It also delves into the system architecture, highlighting the stages involved in the recognition process, such as data preprocessing, character segmentation, and optical character recognition.
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1.2 SCOPE OF THE PAPER The system investigates “Moving Vehicle Number Plate Detection,” centering on the development and implementation of a comprehensive system for real-time identification of vehicle license plates. The study explores the system’s architecture, methodologies, and practical application. It delves into various components such as image processing, object detection, and optical character recognition techniques employed in the system. The paper discusses the system’s features, including its ability to detect moving vehicles, accurately localize license plate regions within the captured frames, and extract alphanumeric character from the license plates using advanced OCR algorithms. Additionally, it examines the
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