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Leaf classification using structure features and Support Vector Machines

机译:使用结构特征和支持向量机对叶子进行分类

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摘要

In Thailand, there are a lot of near extinction herbs, because they are used as an essential resource for food and medicine industry. Before they become extinct, the herb information needs a systematic collection. This paper is proposed a herb leaf classification method for making an automatic categorization. In digitization step, the leaves with white background are photographed with digital camera. As a preprocessing step, apex and leafstalk are removed with a histogram-based method. To describe leaf characteristic, three types of ratio; aspect ratio, slice ratio and radius ratio are measured. These features are scale in variant and −/+15 degrees tolerance of rotation. In experimental results, our technique performs 95 percent accuracy on 10 classes of leaf type.
机译:在泰国,有很多濒临灭绝的草药,因为它们被用作食品和医药工业的重要资源。在它们灭绝之前,草药信息需要系统地收集。提出了一种自动分类的草药叶分类方法。在数字化步骤中,用数码相机拍摄白色背景的叶子。作为预处理步骤,使用基于直方图的方法去除顶点和叶柄。为了描述叶片的特性,三种比例:测量纵横比,切片比和半径比。这些功能具有不同的比例和-/ + 15度的旋转公差。在实验结果中,我们的技术对10种叶片类型执行了95%的精度。

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