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Designing the quality of coffee bean detection application using Hue Saturation Intensity

机译:使用色调饱和强度设计咖啡豆检测应用的质量

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This study discusses the design of applications that can detect the quality of raw coffee beans both good and bad based on the value of HSI(Hue Saturation Intensity)in the coffee beans using digital image processing and Backpropagation artificial neural networks.The process of identifying coffee beans is based on the intensity of the HSI value that is owned by coffee beans.The HSI value is converted from RGB values,then the training process is performed on backpropagation artificial neural networks to recognize good quality seeds and poor-quality seeds.The testing phase is carried out using an interface designed in the MATLAB R2013a software.Based on the results of testing,it was found that this application was able to detect samples of coffee beans that were not properly trained.
机译:本研究讨论了使用数字图像处理和背部化人工神经网络的咖啡豆中的HSI(色调饱和强度)的价值来检测原始咖啡豆质量的应用的设计。识别咖啡的过程 豆类基于咖啡豆所拥有的HSI值的强度.HSI值从RGB值转换,然后对BackProjagation人工神经网络进行培训过程,以识别良好的种子和劣质种子。测试 相位使用在MATLAB R2013A软件中设计的界面进行。基于测试结果,发现该应用程序能够检测咖啡豆的样品,这些豆豆没有受到适当培训的。

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