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首页> 外文期刊>Journal of King Saud University >Presented a fuzzy system to determine barberry product quality based on average color spectra by image processing
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Presented a fuzzy system to determine barberry product quality based on average color spectra by image processing

机译：提出了一种基于平均色谱通过图像处理确定伏牛花产品质量的模糊系统

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摘要

In recent years much research in the field of classification and classification of crops based on characteristics using image processing have been done in this study to determine the level of product quality barberry impurities and the degree of quality we have to use image processing. If the first 100 samples from 10 barberry product quality without gross as the primary data and CMY color mode of the desired color spectrum of each color we set average on the basis of each color a spectrum of color input and output fuzzy variables and fuzzy sets to suit them and determine the appropriate fuzzy rules created brought, then 300 samples of barberry product images with different quality as test data in ourselves and in when testing for accuracy system designed to enhance the image into blocks K * K and the quality of each block based on fuzzy systems implemented quality level of each block separately, and finally we calculate the average rate of making all the block every image quality, the quality of the final product are determined barberry. Based on the experimental results observed by this method was more efficient than previous methods and 98.6% of high precision quality products will determine the barberry.
机译：近年来，在这项研究中，在基于特征的农作物分类和分类领域进行了大量研究，以确定产品质量伏牛花杂质的水平和我们必须使用图像处理的质量程度。如果从10种伏牛花产品质量中获得的前100个样本没有总值作为每种颜色所需色谱的主要数据和CMY色模，则我们将根据每种颜色设置平均值，以使用颜色输入和输出的光谱模糊变量和模糊集适合它们并确定所创建的适当模糊规则，然后将300种不同质量的伏牛花产品图像样本作为我们自己的测试数据，并在进行准确性测试时设计以将图像增强为块K * K，并基于每个块的质量在模糊系统上分别实现每个块的质量水平，最后我们计算出使每个块的每个图像质量的平均速率，最终产品的质量被确定为伏牛花。根据此方法观察到的实验结果，该方法比以前的方法更有效，并且98.6％的高精度品质产品将确定伏牛花。

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