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An Algorithm to Extract Physical Characteristics of Nematodes from Microscopic Images of Plant Roots

机译:一种算法从植物根部微观图像中提取线虫物理特征的算法

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摘要

In Peru, phytoparasite nematodes are a type of specimen that adheres to vegetable roots, preventing plants from absorbing the necessary nutrients to grow. In order to apply contingency and prevention plans, it is necessary to study the families to which the nematode pests belong by analyzing their physical characteristics with a microscope. The proposed system represents an alternative to the current methods for the classification of phytoparasite nematodes through image processing. This system is an algorithm oriented to detect the physical characteristics of nematodes in tropical fruit crops (width and length). The algorithm involves image acquisition of nematodes through a microscope, obtain the luminance component of the image, illumination correction, binarization by histogram, objects segmentation, discrimination by area, surface detection and calculation of the Euclidean distance to approximate the physical characteristics of specimens in a sample of nematodes. Favorable results were obtained in the detection of the characteristics of the Meloidogyne type II species. The results were validated from those obtained by clinical analysis of the specialists, achieving up to 85% of success.
机译:在秘鲁,phytoparasite线虫是一类标本附着于蔬菜根,防止植物不吸收必要的营养生长。为了应用的应急和预防计划,有必要研究该线虫属于用显微镜分析其物理特性的家庭。所提出的系统表示为phytoparasite线虫的通过图像处理得到的分类的当前方法的替代方案。这个系统是面向检测热带水果作物(宽度和长度)线虫的物理特性的算法。所述算法涉及图像获取线虫通过显微镜,获得图像,光量校正,二值化直方图的亮度分量,由面积,表面检测和欧几里德距离的计算对象分割,歧视近似的在一个试样的物理特性样线虫。有利的结果在所述检测的根结线虫II型物种的特性获得的。结果从那些通过了专家的临床分析得到,取得了成功的85%进行了验证。

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