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Research Paper | Computer Science & Engineering | India | Volume 12 Issue 8, August 2023 | Popularity: 5.7 / 10

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Optimizing Pharmaceutical Inventory Management with YoloV7 and Easy OCR on Medicine Strips

Shashwat Kumar, Anannya Chuli

Abstract: This research paper presents a novel two-phase approach for Video Analytics, harnessing the power of OCR to extract vital information from medicine images and videos. In the image phase, YOLOv7 object detection precisely identifies bounding boxes around medicines, complemented by advanced image processing to enhance text extraction accuracy. Leveraging the efficiency of EasyOCR, crucial textual data such as batch numbers, manufacturing dates, expiry dates, and maximum retail prices are extracted and systematically stored in a structured CSV file, enabling seamless identification of expired products. The subsequent video phase employs YOLOv7 for real-time object detection on video frames, effectively identifying bounding boxes around medicines. Leveraging OCR techniques, the system accurately extracts text data from the cropped regions, efficiently stored in a CSV file for seamless integration with other systems. This innovative approach optimizes pharmaceutical inventory management, effectively minimizing losses arising from expired products while enhancing operational efficiency across the phar- maceutical industry. By facilitating data-driven decision-making and streamlined inventory processes, the research showcases the potential for significant improvements in healthcare management and patient care.

Keywords: Video Analytics, OCR (Optical Character Recognition), YOLOv7, Bounding Boxes, Image Processing Techniques, EasyOCR Library, Parsing Techniques

Edition: Volume 12 Issue 8, August 2023

Pages: 1662 - 1669

DOI: https://www.doi.org/10.21275/SR23804233813

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