Some reports indicate counterfeit trafficking represents seven per cent of the world’s trade today, researchers said. While other counterfeit-detection methods exist, these are invasive and run the risk of damaging the products under examination, said researchers including Ashlesh Sharma.A new mechanism that uses algorithms and a smartphone to differentiate between genuine and counterfeit versions of the same product has been developed by a team of Indian-origin researchers in the US. Researchers at New York University (NYU) in the US noted that fake goods represent a massive worldwide problem with nearly every high-valued physical object or product directly affected by this issue.
The new method, by contrast, provides a non-intrusive solution to easily distinguish authentic versions of the product created by the original manufacturer and fake versions of the product made by counterfeiters. It does so by deploying a data set of three million images across various objects and materials such as fabrics, leather, pills, electronics, toys and shoes. ”
The classification accuracy is more than 98 per cent,and we show how our system works with a cellphone to verify the authenticity of everyday objects,” said Lakshminarayanan Subramanian, professor at NYU. “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,” said Subramanian.
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