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PREFAB-GEN : AD HOC IMAGE GENERATION FOR PRE-MANUFACTURING OF TIRES USING IMAGE-TO-IMAGE TRANSLATION

Guillaume Déau, Pascal Bourdon, Philippe Carré, Stéphane Merillou, Alexandre Dervillé, François Mourougaya

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Lecture 11 Oct 2023

In the pneumatic industry, quality control is an essential step in assessing tire compliance. Artificial neural networks are increasingly used to accomplish this task. Their training requires a large number of images of the controlled products. However, at the launch production of a new tire, the lack of images causes a performance loss for the network. To solve this problem, we propose to translate perfect tires computerbased images into ad hoc manufacturing context-realistic ones as pre-manufacturing step to improve robustness and ensure production quality. The challenging work is to extract features in real images and apply them to computer-based images while maintaining the original geometry. In the paper, we propose Prefab-GEN, a novel architecture based on Cycle-GAN. In the generator part, an Inception U-Net architectureis developed to enforce geometrical structure conversion and extract more detailed features. The qualitative and quantitative evaluation on tire dataset shows improvements comparedwith state-of-art.

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