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Sushi Dish - Object detection and classification from real images

2017-10-15
Yeongjin Oh, Seunghyun Son, Gyumin Sim

Abstract

In conveyor belt sushi restaurants, billing is a burdened job because one has to manually count the number of dishes and identify the color of them to calculate the price. In a busy situation, there can be a mistake that customers are overcharged or under-charged. To deal with this problem, we developed a method that automatically identifies the color of dishes and calculate the total price using real images. Our method consists of ellipse fitting and convol-utional neural network. It achieves ellipse detection precision 85% and recall 96% and classification accuracy 92%.

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URL

https://arxiv.org/abs/1709.00751

PDF

https://arxiv.org/pdf/1709.00751


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