Abstract
There is no deny in the fact that duplicate product jeopardizes the luck of businesses worldwide over violating patent rights and causing immense commercial wound. Hence, it has to change into basic for firms to ensure their disgraces opposed to duplication. Existing technologies for electrical forged find encompass the applying of extra security looks prefer Watermark Technology to the emblem stock itself that raises the charges of one’s merchandise. In this paper, a reliable method for counterfeit prediction is proposed. This method can be used by customer to predict counterfeit for their daily need items available in the market. The item may be medicine, detergent or food packet. Now the development of new package of the product always comes with the risk of counterfeiting, sometimes that could affect our health, company reputation and goodwill. We have used the concept of invisible and visible watermarking present in item itself to provide authenticity of the product. This is a low cost solution that help enterprises and consumers identify the authenticity of products.
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Behura, A., Behura, A., Das, H. (2020). Counterfeit Product Detection Analysis and Prevention as Well as Prepackage Coverage Assessment Using Machine Learning. In: Das, H., Pattnaik, P., Rautaray, S., Li, KC. (eds) Progress in Computing, Analytics and Networking. Advances in Intelligent Systems and Computing, vol 1119. Springer, Singapore. https://doi.org/10.1007/978-981-15-2414-1_49
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DOI: https://doi.org/10.1007/978-981-15-2414-1_49
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