Abstract: This project proposes an Automated Vehicle Access Control System that leverages Number Plate Recognition (NPR) technology to identify and authorize vehicles entering a restricted area, such as a university campus or corporate facility. The system captures the vehicle's number plate image using a high-resolution camera positioned at the entry gate. The captured image undergoes grayscale conversion to simplify data processing and reduce computational complexity. Using image processing techniques such as noise removal, edge detection (e.g., Canny or Sobel operators), and segmentation, the number plate region is isolated. Once extracted, the Optical Character Recognition (OCR) module converts the plate's characters into a machine readable text format. This alphanumeric string is then cross-referenced with a predefined database containing authorized vehicle numbers. If a match is found, the system retrieves and displays the stored image of the corresponding vehicle, and the gate control mechanism permits entry. In case of a mismatch, the system displays a "No Access" message and denies entry to the premises.

Keywords: Number Plate Recognition, OCR, Edge Detection, Grayscale Conversion, Access Control System.


Downloads: PDF | DOI: 10.17148/IARJSET.2025.121027

How to Cite:

[1] Afra Furkheen, Vanisha M, Sannidhi Joshi, Sandeep Naidu, Dr. Girish TR, "SMART GATEWAYS: AUTOMATED NUMBER PLATE RECOGNITION FOR SAFER AND SMARTER COMMUNITIES," International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2025.121027

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