Machine Vision for Recognizing Eco-Friendly and Chemical Ink Tags on Garment Labels for Recycling
Abstract
With the increasing demand for sustainable practices in the fashion industry, efficient garment recycling solutions have become essential. One significant challenge in this process is accurately distinguishing garments printed with eco-friendly inks from those printed with chemical-based inks. This study proposes a novel machine vision method for the automatic identification and classification of garments, based on the printing techniques used, as indicated on the garment labels. By embedding a unique ecological ink identifier in the garment's label, this approach leverages advanced image processing techniques to precisely detect and classify the ink type used in the garment's print. This method simplifies the recycling workflow by ensuring accurate classification, reducing manual labour, and improving the overall efficiency of the recycling process. The results demonstrate the feasibility of applying machine vision for garment recycling, the effectiveness of this method in accurately detecting and classifying the ink type used in garment prints, with a high level of precision. The proposed solution proves to be scalable, offering a practical way to enhance the efficiency of garment recycling systems. The integration of machine vision for ink classification in garment recycling holds significant potential for promoting eco-friendly practices in the fashion industry. This automated approach not only simplifies the recycling workflow but also contributes to the broader goal of sustainability by facilitating the proper sorting of garments based on their ink type.
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References
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