首页> 外文会议>International Conference on Industrial Technology and Management >Automated blast disease detection from paddy plant leaf — A color slicing approach
【24h】

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

机译:来自水稻植物叶的自动爆炸疾病检测 - 一种彩色切片方法

获取原文

摘要

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,各种行业正在从手动转移到手中的各种问题的自动化解决方案。然而,这些技术不仅增强了效率,而且还缩短了获得卓越确保卓越所需的成本,时间和劳动力。食品行业现在是一天是涂抹这些技术方面的最重要的地区之一。在农业中,水稻作物是大量田野的主要作物之一,并为食品提供服务。但是,虽然在田野中,这种作物必须面对很多问题,包括营养不良和源于环境条件和害虫的不同疾病。这些问题反过来导致生产的大量损失。可以从农业专业人员遵循专家建议以摆脱这种情况。但远程网站必须面对位置问题,因此从这些问题中受到影响。因此,如果专家通过某些技术手段检查其作物的实际健康状况后,专家可以在不达到该地方的情况下,将是一个更好的方法。本文背后的想法是开发这种算法,可以通过仅通过专家植物叶的图像以及必要的建议/行动来解决水稻作物的爆炸疾病问题。疾病检测算法的后骨是彩色切片技术,其感知患病斑点和损坏的总叶比例,如果疾病存在并在时间内消除它,可以轻松获得建议,以免损失。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号