Automating Security and Next-Gen Surveillance-harnessing Yolov8 and Easyocr Powering Autonomous License Plate Detection Systems

In an era dominated by technological advancements, the amalgamation of cutting-edge innovations in computer vision and artificial intelligence has propelled the evolution of security and surveillance systems to unprecedented heights. Harnessing the power of YOLOv8, an acronym emblematic of its rapid object detection capabilities, and the versatility of EasyOCR for optical character recognition, this paper unveils a paradigm shift in the way license plate detection is conceptualized and implemented. The proposed system not only enhances the accuracy and efficiency of traditional methods but also caters to the dynamic and fast-paced nature of contemporary security challenges. From traffic management to law enforcement and beyond, this proposed system with its impressive Mean Average Precision over 93%, showcases its prowess in elevating security paradigms to unprecedented levels of sophistication. This research not only contributes to the burgeoning field of autonomous security but also establishes a benchmark for the meticulous evaluation of next-generation surveillance technologies.