AL-Biruni Gemstone Authenticator

Abstract

A gemstone is a mineral that is produced from geological processes. All gemstones are either sorted by their colour, nature, or hardness. Gemstones have the potential to make improvement in the export earnings of Pakistan. Gemstones mines inside Pakistan can generate 4-5 or more billion dollars. The complexity of the product is high, audience often suffer loss. It is very difficult to tell difference between real and fake gemstones. The laboratory identification test is time consuming and expensive. There is a need of fast and cheap expert gemstone identification system. The main objective is to create a system that would be able to identify multiple types of gemstone types, namely {Turquoise, Ruby, and Emerald}. AL-biruni Gemstone is gemstones identifier based on machine learning. Machine learning is based on the idea that system can learn from data and forecast prediction on unseen data. Machine learning includes series of learning techniquses—supervised, unsupervised, reinforcement learning. The machine learning technique used for design of model is convolution neural network. The benchmark of the system is to create a system having accuracy more than 90% with large dataset The model has 12 layers.. The hyper parameter tuned is epoch, batch size and learning rate. The learning rate used were 0.001, 0.0001, and 0.00025. The batch sizes were 8, 12, and 16. The Application is developed as prove of concept named Gemo. Gemo android Application is used for integration with machine learning model. The application provides two main features—Authentication and Identification. The authentication features take image as input and return gemstones type as output. The Accuracy of the model used in the application for authentication is 95.0%