Paper Contents
Abstract
While medical technology improves and the application of pharmaceuticals is increasingly used, pill identification has become of major importance. Identification of drugs as being the right ones for patients is so much critical for patient safety, reducing the occurrence of prescription mistakes, and preventing the flow of fake drugs. In this work, we present a computer vision and deep learning-based system for detecting and identifying pills from their visual featuresshape, color, and imprinted text. The method that integrates the Convolutional Neural Networks (CNN), optical character recognition (OCR), and image processing to develop a consistent identification model. This AI system is integrated into an easy-to-use web interface for real-time pill identification and accessibility. Our model was thoroughly evaluated with diverse data sets and performed well with high accuracy, indicates promise in potential for use in actual real-world healthcare settings. Apart from technical performance, the research also discusses practical concerns, limitations, and the ethical implication of implementing such technology within clinical environments.
Copyright
Copyright © 2025 Chethan Kumar S. This is an open access article distributed under the Creative Commons Attribution License.
