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Classification of selected medicinal plant leaves using texture analysis

机译:使用纹理分析对药用药用植物叶片进行分类

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Plants play one of the most important roles in our ecosystem. But the rapid decline in the variety of plants is an issue which demands our immediate attention. The first logical step would be the identification of the different plant species by the botanists. Manual identification can often be time consuming and inaccurate. Plants also play a major role in ayurvedic and modern forms of medicine. There is an urgent need to identify and classify the medicinal plants. For this purpose we need an automated and reliable tool which can easily identify and classify plants using available information. So this paper aims at developing such a method to identify and classify medicinal plants from their leaf images using texture analysis of the images as a basis for classification. The software identifies and returns the closest match of the query image from the database based on its texture features. Next the texture features obtained by texture analysis are tested individually on the test leaves to identify the most efficient among them. A combination of these texture features is used for classification and the success rate is recorded.
机译:在我们的生态系统中,植物扮演着最重要的角色之一。但是植物种类的迅速减少是一个需要我们立即注意的问题。逻辑上的第一步是植物学家确定不同的植物物种。手动识别通常很耗时且不准确。植物在印度草药疗法和现代医学形式中也起着重要作用。迫切需要对药用植物进行识别和分类。为此,我们需要一个自动化且可靠的工具,该工具可以使用可用信息轻松地对植物进行识别和分类。因此,本文旨在开发一种利用其图像纹理分析作为分类基础,从叶片图像中识别和分类药用植物的方法。该软件根据其纹理特征从数据库中识别并返回最接近查询图像的匹配项。接下来,将通过纹理分析获得的纹理特征分别在测试叶上进行测试,以找出其中最有效的特征。这些纹理特征的组合用于分类,并记录成功率。

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