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Non-destructive Quality Evaluation Technique for Processed Phyllanthus Emblica(Gooseberry) Using Image Processing

机译:图像处理的余甘子(醋栗)无损质量评价技术

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This paper proposes non-destructive quality evaluation method to categorize a processed phyllanthus emblica (gooseberry) using image processing by color and texture features. Russia is one of the most important gooseberry producers in North Asia, than Germany, Poland, U.K, India etc, but fruit sorting in some area is still done by hand which is tedious and inaccurate. Thus, the need exists for improvement of efficiency and accuracy of this fruit quality assessment that can meet the demands of international markets. Low-cost and non-destructive technologies capable of sorting processed gooseberry according to their properties would help to promote the gooseberry export industries. This paper propose the method of colorization and extracting value parameters, by this parameters the detection of browning or affected part and identification of the uniform shape and size. This differentiate the quality of processed gooseberries.
机译:本文提出了一种无损质量评价方法,通过颜色和纹理特征对经过处理的余甘子(猕猴桃)进行图像处理。与德国,波兰,英国,印度等相比,俄罗斯是北亚最重要的猕猴桃生产国之一,但某些地区的水果分拣仍然是手工完成的,既繁琐又不准确。因此,需要提高这种水果质量评估的效率和准确性,以满足国际市场的需求。能够根据加工后的醋栗的特性分类的低成本无损技术将有助于促进醋栗的出口产业。本文提出了一种着色和提取值参数的方法,通过该参数可以检测出褐变或受影响的部分,并识别出均匀的形状和大小。这可以区别加工醋栗的质量。

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