Machine Learning approach to identify Gemstones and their shape

Abstract

"The gemstone business is filled with difficulties, particularly the widespread problem of distinguishing genuine gemstones from counterfeit imitations, which are frequently carefully made to look like the real thing. This deceitful method erodes consumer trust and confidence, requiring strong solutions to differentiate authentic gemstones from counterfeit ones. Moreover, the task of differentiating between different gem cuts presents a substantial difficulty, hence adding complexity to the buying process for purchasers. To address these urgent concerns, thorough research project focused on solving the dual problems of gemstone identification and shape recognition. By utilising advanced image processing techniques and machine learning approaches, specifically, Convolutional Neural Networks (CNNs), created a complex classification system that can effectively identify the name of the gemstone with high accuracy. In addition, by employing novel methods for identifying gem shapes, which involve the utilisation of shape recognition and Photogrammetry principles, the aim is to equip consumers with the necessary information to make well-informed purchasing choices. This research highlights the significance of technical innovation in reducing fraudulent practices in the gem industry. The goal is to improve transparency and rebuild trust in the gemstone industry by offering purchasers dependable tools for gemstone authentication and cut recognition. This will create a fair and secure trading environment for all parties concerned."