阿育吠陀药用植物叶样图像处理鉴定

P. Manoj Kumar, C. M. Surya, Varun P. Gopi
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引用次数: 56

摘要

在阿育吠陀医药工业中,确定正确的药用植物是非常重要的。鉴别药用植物的主要特征是叶子的形状、颜色和质地。叶子两侧的颜色和纹理包含确定的参数来识别物种。本文探索了绿叶正面和背面的特征向量以及形态特征,以获得最大识别率的独特最佳特征组合。通过对常用阿育吠陀药用植物叶片正面和背面的扫描图像,建立药用植物叶片数据库。根据树叶独特的特征组合进行分类。识别率高达99%已获得测试时,在广泛的分类器。将上述工作扩展到包括干叶识别,并获得特征向量组合,使用该组合,识别率超过94%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of ayurvedic medicinal plants by image processing of leaf samples
Identification of the correct medicinal plants that goes in to the preparation of a medicine is very important in ayurvedic medicinal industry. The main features required to identify a medicinal plant is its leaf shape, colour and texture. Colour and texture from both sides of the leaf contain deterministic parameters to identify the species. This paper explores feature vectors from both the front and back side of a green leaf along with morphological features to arrive at a unique optimum combination of features that maximizes the identification rate. A database of medicinal plant leaves is created from scanned images of front and back side of leaves of commonly used ayurvedic medicinal plants. The leaves are classified based on the unique feature combination. Identification rates up to 99% have been obtained when tested over a wide spectrum of classifiers. The above work has been extended to include identification by dry leaves and a combination of feature vectors is obtained, using which, identification rates exceeding 94% have been achieved.
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