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.
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.
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 dataset 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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