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An Efficient Method for Quality Analysis of Rice Using Machine Vision System

机译:用机器视觉系统一种高效的水稻质量分析方法

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摘要

Agricultural industry is the oldest industry in the world. There are numerous challenges faced by this industry in proper quality analysis. Quality assessment of grains is a very big challenge for a long time. This paper presents a solution for quality assessment and grading of Indian basmati Oryza sativa L variety rice using machine vision and image processing. Basic problem of rice industry for quality assessment is addressed which is traditionally done manually by human inspectors. Machine vision provides an alternative with automated, non-destructive, cost-effective, and fast approach method. Quality analysis is done using computer vision, image analysis and processing as compared to human vision inspection. This paper presents an efficient method for calculating the size of Oryza sativa L rice using machine vision along with detection of chalky and broken rice with improved accuracy compared with human inspectors.
机译:农业产业是世界上最古老的行业。 在适当的质量分析中,这个行业面临着许多挑战。 谷物的质量评估很长一段时间都是一个非常重要的挑战。 本文介绍了使用机器视觉和图像处理的印度巴斯马蒂奥里扎苜蓿品种米的质量评估和分级的解决方案。 解决了质量评估水稻行业的基本问题,传统上由人类检查员手动完成。 机器愿景提供了一种自动化,无损性,经济高效和快速接近方法的替代方案。 与人类视觉检查相比,使用计算机视觉,图像分析和处理进行质量分析。 本文介绍了使用机器视觉计算Oryza Sativa L米的尺寸的有效方法,以及与人类检查员相比,通过改善的精度提高了Chalky和破碎的水稻。

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    Electronics and Communication Engineering Department Sant Longowal Institute of Engineering and Technology Longowal-148106 Punjab India;

    Electronics and Communication Engineering Department Sant Longowal Institute of Engineering and Technology Longowal-148106 Punjab India;

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  • 正文语种 eng
  • 中图分类 计量学;
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