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Pizza quality evaluation using computer vision―part 1 Pizza base and sauce spread

机译:使用计算机视觉进行比萨质量评估-第1部分:比萨基础和酱汁涂抹

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摘要

The growth in the popularity and consumption of pizzas has led to the need for automated quality inspection, so as to maintain confidence and increase production efficiency. In the current research the use of computer vision for inspection of pizza base and tomato sauce spread quality was investigated. Twenty pizza bases were analysed for base area, spatial ratio Ⅰ (SRI), spatial ratio Ⅱ (SRII), and circularity. For the measurement of the sauce spread characteristics based on 25 samples, the indexes taken were sauce area and heavy area percentage; a fuzzy logic system was then developed to classify the sauce spread samples into classes of acceptable and defective quality. The base area analysis gave a classification error of 13% when compared to human assessment. The experimental results for the sauce spread analysis show that by using computer vision in conjunction with fuzzy logic a classification accuracy of 92% can be achieved.
机译:披萨的受欢迎程度和消费量的增长导致需要进行自动质量检查,以保持信心并提高生产效率。在当前的研究中,研究了使用计算机视觉检查比萨饼基料和番茄酱的涂抹质量。分析了20个比萨饼的底部面积,空间比率Ⅰ(SRI),空间比率Ⅱ(SRII)和圆形度。为了测量基于25个样品的酱汁传播特性,所采用的指标是酱汁面积和重面积百分比;然后开发了一个模糊逻辑系统,将酱汁涂抹样品分类为可接受和有缺陷的质量类别。与人工评估相比,基础面积分析得出的分类错误为13%。酱汁涂抹分析的实验结果表明,通过将计算机视觉与模糊逻辑结合使用,可以实现92%的分类精度。

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