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Novel algorithm for segmentation and automatic identification of pests on plants using image processing

机译:使用图像处理的分割和植物害虫自动识别的新算法

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Enormous agricultural yield is lost every year, due to rapid infestation by pests and insects. A lot of research is being carried out worldwide to identify scientific methodologies for early detection/identification of these bio-aggressors. In the recent past, several approaches based on automation and image processing have come to light to address this issue. Most of the algorithms concentrate on pest identification and detection, limited to a greenhouse environment. Also, they involve several complex calculations to achieve the same. In this paper, we propose a novel and unique algorithm to segregate and detect pests using image processing. The proposed methodology involves reduced computational complexity and aims at pest detection not only in a greenhouse environment but also in a farm environment as well. The whitefly, a bio-aggressor which poses a threat to a multitude of crops, was chosen as the pest of interest in this paper. The algorithm was tested for several whiteflies affecting different leaves and an accuracy of 96% of whitefly detection was achieved. The algorithm was developed and implemented using MATLAB programming language on MATLAB 7.1 build 2011a.
机译:由于害虫和昆虫快速侵染,每年都会失去巨大的农业收益率。在全球范围内进行了许多研究,以确定用于早期检测/识别这些生物侵略者的科学方法。在最近的过去,基于自动化和图像处理的几种方法都有光明来解决这个问题。大多数算法集中在害虫鉴定和检测上,限于温室环境。此外,它们涉及几个复杂的计算来实现相同的计算。在本文中,我们提出了一种使用图像处理分离和检测害虫的新颖和独特的算法。所提出的方法涉及降低的计算复杂性,并瞄准害虫检测,不仅在温室环境中也是在农场环境中。粉虱是一种对众多作物构成威胁的生物侵略者,被选为本文的兴趣害虫。对影响不同叶片的几个粉虱测试了该算法,实现了96%的粉虱检测的准确度。使用Matlab 7.1 Build 2011a的Matlab编程语言开发和实现了该算法。

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