International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Automatic Number Plate Recognition System for Real-Time Vehicle Entry and Exit Logging Using YOLO and EasyOCR |
|---|---|
| ABSTRACT | Vehicle monitoring and access control systems are critical for security, traffic control, and vehicle movement records in residential complexes, offices, campuses, commercial buildings, and restricted zones. As vehicle usage increases, manual entry and exit logging becomes error-prone, slow, and difficult to manage. This paper presents an Automatic Number Plate Recognition (ANPR) System designed to automate vehicle number plate detection, OCR-based text extraction, and digital entry/exit event logging. The system employs a YOLO-based object detection model for number plate localization and EasyOCR for character recognition. A Python Flask web application provides a responsive, browser-based user interface for uploading images or video inputs. Detected plates and event records are stored in an Excel database using OpenPyXL. Experimental evaluation across multiple test scenarios demonstrates a detection and recognition accuracy of 90–95% under standard conditions, with a custom-trained YOLO model achieving approximately 93.5% accuracy. Compared to manual logging, the ANPR system reduces average processing time from 5–10 seconds to under 2 seconds per vehicle and significantly reduces human error. The proposed system provides a scalable, intelligent, and efficient solution for smart vehicle surveillance and access control. |
| AUTHOR | A. RISHVAN, P. VINCENT, S. ESAKKI SARAN, R. NARMATHA Department of Artificial Intelligence and Data Science, Christ the King Engineering College, Coimbatore, Tamil Nadu, India Assistant Professor, Department of Artificial Intelligence and Data Science, Christ the King Engineering College, Coimbatore, Tamil Nadu, India |
| VOLUME | 184 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1405037 |
| pdf/37_Automatic Number Plate Recognition System for Real-Time Vehicle Entry and Exit Logging Using YOLO and EasyOCR.pdf | |
| KEYWORDS | |
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