<![CDATA[Vehicle license plate recognition plays a vital role in intelligent transportation systems, parking management, and digital ticketing. However, conventional license plate recognition systems often face challenges related to lighting variations, viewing angles, and character distortions, which can decrease accuracy and efficiency, especially on mobile devices. This study aims to implement an Optical Character Recognition (OCR) framework, specifically EasyOCR, in a mobile application designed to read vehicle license plates in real time. The system was developed using the Software Development Life Cycle (SDLC) methodology, which includes the stages of planning, analysis, design, implementation, and testing. The mobile application was built using Flutter, integrated with a smartphone camera for data input and EasyOCR for text extraction. The testing results demonstrate that the proposed system can accurately detect and recognize license plate characters with an average accuracy rate of 100%. The contribution of this study lies in the application of EasyOCR on mobile platforms through a structured SDLC approach, enhancing the practicality of OCR-based vehicle identification systems for real-world transportation and parking management applications.]]>
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