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A brief study on paddy applications with image processing and proposed architecture

机译：稻田应用的图像处理和拟议架构的简要研究

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摘要

Agriculture industry is one of the main economic activities in Asean countries. The activities involved a lot of crop planting and yield production in paddy, rubber, oil palm and so forth. Meanwhile in Malaysia, paddy is the third most widely planted crop after oil palm and rubber. Rice, produced by paddy, is considered to be one of Malaysia and Asean staple food and cereal crops. Due to its importance, there are a lot of efforts to ensure its safety, by having crop management of paddy plants such as, disease early detection system. The conventional way to detect plant defects is through human vision and it requires deep knowledge and understanding of the plant. The knowledge is gained through years of experience and observation. Therefore, the intelligent methods in this research are expected to assist the farmers in identifying leaf diseases. In this paper, we present the studies that deployed image processing technologies in paddy domain. Subsequently, we propose the architecture of our system for identifying the early stage of the leaf diseases and finding the weed species. The proposed system is expected to reduce the risk of diseases from becoming worse which may minimize the paddy yields.
机译：农业产业是东盟国家的主要经济活动之一。这些活动涉及稻田，橡胶，油棕等的大量作物种植和产量生产。与此同时，在马来西亚，帕迪是油棕和橡胶后第三种植种植的作物。稻迪生产的米饭被认为是马来西亚和东盟主食和谷物作物之一。由于其重要性，通过在诸如疾病早期检测系统等疾病的稻草的作物管理，有很多努力确保其安全。检测植物缺陷的常规方法是通过人类视觉，并且需要深入的知识和对植物的理解。通过多年的经验和观察获得知识。因此，预计本研究中的智能方法可以帮助农民识别叶片疾病。在本文中，我们介绍了稻田中部署图像处理技术的研究。随后，我们提出了我们的系统的建筑，用于鉴定叶片疾病的早期阶段并找到杂草物种。预计建议的系统将降低疾病的风险变得更糟，这可能会使水稻产量最小化。

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