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Automated blast disease detection from paddy plant leaf — A color slicing approach

机译:水稻叶片自动瘟病检测—彩色切片方法

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In the era of technology, the various industries are shifting from manual to automated solutions of various problems in the hand. Whereas these techniques has not only augmented the efficiency, they also have shortened the cost, time and labor hours required to get an assured excellence. Food Industry now a days is one of the foremost areas smearing these technology aspects. In agriculture the paddy crop of is one of the major crops casing large amount of fields and serving the food necessities. But while in field this crop has to face a lot of problems which include malnutrition and different diseases originated from environmental conditions and pests too. These problems in turn cause a large loss to the produce. An expert advice may be followed on from the agriculture professionals to get rid of such circumstances. But the remote sites has to face the location problems and hence get affected from such issues. So it will be a much better approach if they can be advised by the experts after checking the actual health status of their crop via some technological means without reaching at the place. The idea behind this paper is to develop such an algorithm which can work out for the problem of Blast Disease of paddy crops by just examining the image of plant leaf by the experts along with necessary advice/action. The back bone of the disease detection algorithm is Color Slicing Technique which perceives the diseased spots and damaged proportion of total leaf, making it easy to get advice if disease exists and eliminate it within time so as to avoid losses.
机译:在技​​术时代,各行各业都从手工解决手工问题转变为自动化解决方案。这些技术不仅提高了效率,而且还缩短了获得可靠的卓越性能所需的成本,时间和劳动时间。现在,食品工业是涂抹这些技术方面的最重要领域之一。在农业中,稻谷作物是覆盖大量田地并满足食品需求的主要作物之一。但是在田间,这种作物必须面对许多问题,包括营养不良以及环境条件和害虫引起的各种疾病。这些问题继而导致农产品的大量损失。可以遵循农业专家的建议,以消除这种情况。但是远程站点必须面对位置问题,因此会受到此类问题的影响。因此,如果专家通过某种技术手段检查了农作物的实际健康状况后,专家可以在不到达现场的情况下为他们提供建议,那将是一个更好的方法。本文背后的想法是开发这样一种算法,仅需由专家检查植物叶片的图像以及必要的建议/措施,便可以解决稻瘟病的问题。疾病检测算法的后骨是彩色切片技术,该技术可以感知病斑和总叶子的受损比例,从而很容易获得疾病的建议并及时消除,以免造成损失。

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