Indian-origin researchers have developed a new system that uses Artificial Intelligence algorithms and a smartphone app to instantly distinguish between genuine and fake versions of the same product.
The system works by deploying a dataset of three million images across various objects and materials such as fabrics, leather, pills, electronics, toys and shoes.
98% accuracy
“The classification accuracy is more than 98%, and we show how our system works with a cellphone to verify the authenticity of everyday objects,” said Lakshminarayanan Subramanian, professor at New York University.
The system is scheduled to be presented on August 14 at the annual KDD Conference on Knowledge Discovery and Data Mining in Halifax, Nova Scotia, Canada.
The system described in the presentation is commercialised by Entrupy Inc., an New York University start-up founded by Ashlesh Sharma, Vidyuth Srinivasan, and Subramanian.
Detecting fake products with Entrupy is easy. One has to place the device directly on the item, open the Entrupy app on smartphone or tablet (iOS), and follow the onscreen prompts in the app to take images.
The Artificial Intelligence algorithms then analyse the images to determine authenticity and provide results in real-time. “The underlying principle of our system stems from the idea that microscopic characteristics in a genuine product or a class of products — corresponding to the same larger product line-exhibit inherent similarities that can be used to distinguish these products from their corresponding counterfeit versions,” Mr. Subramanian explained.
Counterfeit goods represent a massive worldwide problem with nearly every high-valued physical object or product directly affected by this issue, the researchers noted.
The Entrupy method provides a non-intrusive solution to easily distinguish authentic versions of the product produced by the original manufacturer and fake versions of the product produced by counterfeiters.
