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Automatic Identification of Botanical Samples of leaves using Computer Vision

机译:使用计算机视觉自动识别叶片的植物样本

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Leaf can be one of the many different parameters on the basis of which a plant can be uniquely identified. Many plants types are on the verge of extinction and can be taken care of, if identified correctly. The proposed method discusses an automated image processing system for leaf classification. The leaf pixels from the image are segmented and termed as region of interest (ROI). A set of geometrical, textural and statistical features is extracted for each input sample and analyzed using a multi class SVM classifier. The proposed system has achieved an accuracy of 97% with a sensitivity of 98.32%. The results are encouraging for a dataset consisting of 10 different leaf classes and can be used for development of some real time application.
机译:叶子可以是众多不同参数之一,其中可以唯一地识别工厂。许多植物类型在濒临灭绝的边缘,如果正确识别,可以处理。该方法讨论了用于叶分类的自动图像处理系统。来自图像的叶片像素被分段并称为感兴趣区域(ROI)。为每个输入样本提取一组几何,纹理和统计特征,并使用多类SVM分类器进行分析。所提出的系统已经实现了97 %的精度,灵敏度为98.32 %。结果令人鼓舞的数据集由10个不同的叶片类别组成,可用于开发一些实时应用。

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