ENHANCING THE EFFICIENCY OF LICENSE PLATE DETECTION USING YOLO AND OPTICAL CHARACTER RECOGNITION Articles
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Abstract
This research aims to 1) develop and enhance license plate detection using YOLO and Optical Character Recognition (EasyOCR) and 2) study and find techniques and algorithms that are accurate and efficient for system design and development. The research employs image processing techniques that include converting images to grayscale, applying Gaussian blur, edge detection using Sobel, binary image analysis, line detection, and image cleanup using morphological processing. The experiments utilized a total of 100 license plate images, and the proposed method achieved an average detection accuracy of 95.26% and a reading accuracy of 78.68%, respectively.
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This article is published and copyrighted by the Science and Technology Journal. South East Bangkok College
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