OCR Driven Intelligent Tablet Segregator and Structured Row Placement

The proposed work presents an OCR-powered tablet segregator and row placement system designed to optimize medication organization in pharmacies. Manual sorting of tablets is often time-consuming and prone to errors, leading to inefficiencies and potential misplacement of drugs. To address this, the system uses advanced Optical Character Recognition (OCR) powered by artificial intelligence to identify tablet names from images of their packaging. These images, either captured manually or sourced online, undergo preprocessing to standardize resolution and remove noise, ensuring accurate text extraction. Once the tablet name is recognized, the system categorizes and assigns the tablet to a predefined storage row, eliminating the need for manual intervention. A voice announcement module further enhances usability by audibly communicating the correct placement location, making the system more accessible and pharmacist-friendly. The proposed solution is cost-effective, scalable, and user-centric, aimed at reducing human error and labor dependency while increasing efficiency and safety. Its adaptability makes it well-suited for real-world deployment in modern pharmacy environments. Key Terms – OCR-powered Optical Character Recognition (OCR), Automated tablet segregation, Pharmacy workflow optimization, Voice-assisted placement system.