A neural network based counterfeit detection system to verify the authenticity o...
A neural network based counterfeit detection system to verify the authenticity of products
Counterfeiting is a crime, involving the manufacturing or distribution of goods under someone else's name, and without their permission. Counterfeit goods are generally made from cheap and lower quality component that put the heal...
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Información proyecto Microguard
Duración del proyecto: 3 meses
Fecha Inicio: 2018-05-31
Fecha Fin: 2018-09-30
Líder del proyecto
CYPHEME
No se ha especificado una descripción o un objeto social para esta compañía.
TRL
4-5
Presupuesto del proyecto
71K€
Fecha límite de participación
Sin fecha límite de participación.
Descripción del proyecto
Counterfeiting is a crime, involving the manufacturing or distribution of goods under someone else's name, and without their permission. Counterfeit goods are generally made from cheap and lower quality component that put the health and safety of consumers at risk.
According to an International Chamber of Commerce the total value of counterfeit and pirated goods globally is around €1.77 trillion. Each year EU companies lose €83 billion in sales due to counterfeited products. Although the counterfeiting has been a problem for decades, there is no solution yet for it fighting at consumer level.
Cypheme introduces a counterfeit detection system that allows a consumer to determine if a product is an original branded product using only a cell phone camera. The system uses a micro structured varnish that can only be read with a neural network technology developed by Cypheme to authenticate the product. The system can be applied directly on the product, making it harder for counterfeiters to copy.
During the feasibility assessment, a minimum viable product will be defined, a go-to-market strategy and a supply chain will be established, as well as further development plan will be drafted. Within the overall innovation project, Cypheme aims to adapt the varnish application to metal, glass and plastic and upscale the neural recognition software; optimize the user interface for brand owners and consumers; perform a quality demonstration and validation of the system at different goods.