Beauty Formula DermoScan: user-centric skincare products’ ingredient analysis platform

daily skincare routines play a pivotal role in determining the long-term health and appearance of one's skin. The presence of synthetic chemicals in numerous skincare products can lead to various adverse effects for consumers, which may result in skin allergies. Consequently, a deep understanding of skincare products and their ingredients becomes essential. This knowledge empowers individuals to craft personalized skincare regimens that effectively target their unique concerns and complement the professional care they receive. This research addresses the limited accessibility of information about the intricate chemical compositions of skincare products for consumers and stakeholders. In response, this study integrates Optical Character Recognition (OCR) technology, machine learning algorithms; TF-IDF text matching technique and KNN text categorization algorithm, and visualization techniques. The overarching goal is to establish a user-centric website, "Beauty Formula DermoScan," providing a seamless solution for users to comprehend skincare ingredients. Through a simple photo upload, users receive detailed and easily understandable insights into the product's composition. This comprehensive approach seeks to revolutionize the skincare industry by fostering transparency, efficiency, and a knowledge-driven ecosystem. Beauty Formula DermoScan can redefine how both consumers and the industry perceive and engage with skincare ingredients, offering a transformative platform for informed decision-making.