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首页> 外文会议>International Conference on Soft Computing and Pattern Recognition >Leaf Shape Identification of Medicinal Leaves using Curvilinear Shape Descriptor
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Leaf Shape Identification of Medicinal Leaves using Curvilinear Shape Descriptor

机译：使用曲线形状描述叶片形状鉴定药物

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摘要

This study proposes a new algorithm for leaf shape identification of medicinal leaves based on curvilinear shape descriptor. Leaf shape is a very discriminating feature for identification. The proposed approach is introduced to recognize and locate points of local maxima from smooth curvature and also to reduce contour points in order to optimize the efficiency of leaf shape identification. Experiments were conducted on six shapes of medicinal leaves, i.e lanceolate, ovate, obovate, reniform, cordate, and deltoid. We extracted live shape descriptors of leaf shape curvature: salient points' position, centroid distance, extreme curvature, angle of curvature, and slope of salient points. The experimental results show that the proposed algorithm can extract the shape descriptors for leaf shape identification. Moreover, the experimental results indicated that the fusion of shape descriptors outperform than using single shape descriptor with accuracy 72.22%.
机译：本研究提出了一种基于曲线形状描述符的药物叶片形状识别算法。叶形是一个非常辨别的特征。介绍所提出的方法，以识别和定位局部最大值的点，从平滑的曲率和减少轮廓点以优化叶形识别的效率。实验是在六种药物叶片上进行的，即披针形，卵形，卵形，肾状，肠道和三角石。我们提取了叶片形状曲率的活形状描述符：突出点的位置，质心距离，极端曲率，曲率角度和凸起的斜率。实验结果表明，该算法可以提取用于叶形识别的形状描述符。此外，实验结果表明，形状描述符的熔化比使用单个形状描述符，精度为72.22％。

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