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Non-destructive Quality Analysis of Indian Basmati Oryza Sativa SSP Indica (Rice) Using Image Processing

机译:利用图像处理技术对印度香米(Sastiva)S稻(大米)的无损质量分析

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The Agricultural industry on the whole is ancient so far. Quality assessment of grains is a very big challenge since time immemorial. The paper presents a solution for quality evaluation and grading of Rice industry using computer vision and image processing. In this paper basic problem of rice industry for quality assessment is defined which is traditionally done manually by human inspector. Machine vision provides one alternative for an automated, non-destructive and cost-effective technique. With the help of proposed method for solution of quality assessment via computer vision, image analysis and processing there is a high degree of quality achieved as compared to human vision inspection. This paper proposes a new method for counting the number of Oryza sativa L (rice seeds) with long seeds as well as small seeds using image processing with a high degree of quality and then quantify the same for the rice seeds based on combined measurements.
机译:到目前为止,农业总体上是古老的。自远古时代以来,谷物的质量评估是一个很大的挑战。本文提出了一种利用计算机视觉和图像处理技术对稻米行业进行质量评估和分级的解决方案。本文定义了大米行业用于质量评估的基本问题,传统上这是由检查员手动完成的。机器视觉为自动化,无损且经济高效的技术提供了一种选择。借助于所提出的用于通过计算机视觉,图像分析和处理解决质量评估的方法,与人类视觉检测相比,可以实现较高的质量。本文提出了一种新的方法,该方法利用高质量的图像处理技术来计算长种子和小种子的水稻种子的数量,然后基于联合测量对水稻种子进行量化。

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