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Rice Spikelet Yield Determination Using Image Processing

机译:利用图像处理技术测定水稻小穗产量

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摘要

There is a lot of Philippines rice varieties that need profiling according to Philippine Rice Research Institute (IRRI) [1]. While current methodology involves manual process and normally takes more than a week to complete, improving and developing a new variety is thus slower due to this aspect. This study proposes an automatic technique to perform profiling of rice spikelets using camera system and image processing technology. The system automatically counts and separates filled and unfilled rice spikelets using a camera, analyze the captured spikelet image by image processing, view and control the resulting data through a graphical user interface specifically designed to cater user's needs. Different varieties of rice samples are tested and validated with the current methodology. Result from 30 samples for each rice variety showed device accuracy of more than 95% was obtained.
机译:根据菲律宾水稻研究所(IRRI)[1],有许多菲律宾水稻品种需要分析。尽管当前的方法学涉及人工过程,通常需要一个多星期才能完成,但是由于这方面的原因,改进和开发新品种的速度较慢。这项研究提出了一种自动技术,利用相机系统和图像处理技术对水稻小穗进行分析。该系统使用摄像头自动计数和分离填充和未填充的水稻小穗,通过图像处理分析捕获的小穗图像,通过专门设计用于满足用户需求的图形用户界面查看和控制结果数据。使用当前方法对不同品种的大米样品进行了测试和验证。每个水稻品种的30个样品的结果表明,设备准确度超过95%。

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