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Freshness Detection Of Snake Fruit Using A Combination Of Gaussian Classifier and FCM

机译:基于高斯分类器和FCM的蛇果新鲜度检测

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This research is focused on developing analysis to handle the problem of freshness detection of snake fruit variant pondoh. Snake fruit has a change of color and a shape that is not very significant if viewed from the skin, but naturally in the Snake fruit has a sign of minor changes that can be used as a benchmark of the freshness level of snake fruit in the head of white skin on the snake fruit will change color from white to dark color, this change signifies the process of rotting in snake fruit. Thus developed the detection of the freshness level of snake fruit by implementing a combination of Gaussian classifier and fuzzy c-mean in the analysis of browning index, texture and color contrast by taking a sample of snake fruit image. The results of this research can be used to help see the freshness of snake fruit without having to peel its skin. From the manual way to see the freshness of snake fruit the way it is seen, smelled and pressed fruit this can make the fruit contaminated and reduce the freshness of snake fruit, which in this research can be shortened the process and represented by taking snake fruit image only.
机译:这项研究的重点是开发分析方法,以处理蛇果变种potanh的新鲜度检测问题。从皮肤上看,蛇果实的颜色和形状变化不明显,但是蛇果实自然具有细微变化的迹象,可以用作蛇头果实头部新鲜度的基准。蛇果上的白色皮肤将从白色变为深色,这种变化表示蛇果腐烂的过程。因此,通过将高斯分类器和模糊c均值相结合,对蛇果图像的褐变指数,质地和颜色对比度进行分析,从而开发了对蛇果新鲜度的检测方法。这项研究的结果可用于帮助了解蛇果的新鲜度,而不必去皮。从人工观察蛇果的新鲜度,观察,闻到和压榨水果的方式可以使水果受到污染并降低蛇果的新鲜度,在本研究中可以缩短加工过程并以蛇果为代表仅图像。

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