000			02129nam a22001817a 4500
003			OSt
005			20240919142159.0
008			240905b |||||||| |||| 00| 0 eng d
040			_aMMSU _cULS
100			_aCastaño, Charles Philip E...et.al.
245			_aLicense plate recognition system using computer vision for profiling vehicle entering and exiting Mariano Marcos State University / _cCharles Philip E. Castaño, Julianna D. Estavillo, Noemie Leigh G. Laforga, Stacy Khaye C. Rodrigo & Carlie Jane L. Ronque
260			_aCity of Batac : _bMMSU, _c2024.
300			_axxi, 124 leaves : _c29 cm
500			_aUTHESIS ( Bachelor of Science in Computer Engineering)
504			_aBibliography: leaves 79-81
520			_aThis thesis introduces an innovative approach by integrating YOLOv8, a state-of-the-art object detection model, into a License Plate Recognition (LPR) system for profiling vehicles at Mariano Marcos State University (MMSU). The system uses advanced computer vision techniques to capture and recognize license plates through strategica ly placed cameras at the entry and exit points of the university. The process involves image processing, license plate localization, character segmentation, and Optical Character Recognition (OCR), all enhanced byYOLOv8 for accurate retrieval of alphanumeric characters. The study followed a three-phase approach: pre-planning, development, and evaluation. Pre-planning involved setting objectives and methods; development encompassed executing methodologies and co lecting data; and evaluation focused on data analysis and drawing conclusions. xxiv Evaluation of the system is based on its effectiveness, accuracy, and dependability yielded promising results, affirming its success. Each criterion received a highly functional rating percentage- effectiveness, accuracy and dependability demonstrating the robust performance of the system. In conclusion, integrating YOLOv8 into the LPR system significantly advances vehicle profiling technology, making it a valuable asset for MMSU by enhancing campussecurity and safety
942			_2lcc _cTHEDIS
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