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Embedded portable device for herb leaves recognition using image processing techniques and neural network algorithm.

机译:使用图像处理技术和神经网络算法的嵌入式便携式草叶识别设备。

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摘要

Herbs have been widely used in food preparation, medicine and cosmetic industry. Knowing which herbs to be used would be very critical in these applications. Nevertheless, the current way of identification and determination of the types of herbs is still being done manually and prone to human error. Designing a convenient and automatic recognition system of herbs species is essential since this will improve herb species classification efficiency. This research focus on recognition approach to the shape and texture features of the herbs leaves. It aims to realize the computerized method to classify the herbs plants in a very convenient way. Portable herb leaves recognition system through image and data processing techniques is implemented as automated herb plant classification system. It is very easy to use and inexpensive system designed especially for helping scientist in agricultural field. The proposed system employs neural networks algorithm and image processing techniques to perform recognition on twenty species of herbs. One hundred samples for each species went through the system and the recognition accuracy was at 98.9%. Most importantly the system is capable of identifying the herbs leaves species even though they are dried, wet, torn or deformed. The efficiency and effectiveness of the proposed method in recognizing and classifying the different herbs species is demonstrated by experiments. All rights reserved, Elsevier.
机译:草药已广泛用于食品制备,医药和化妆品行业。在这些应用中,知道要使用哪种草药至关重要。尽管如此,目前鉴定和确定草药类型的方法仍是手动完成的,并且容易出现人为错误。设计一种方便且自动的草药种类识别系统至关重要,因为这将提高草药种类的分类效率。这项研究集中于对草药叶的形状和纹理特征的识别方法。它的目的是实现一种非常方便的方法来对草药植物进行分类的计算机化方法。通过图像和数据处理技术的便携式药草叶识别系统被实现为自动药草植物分类系统。它非常易于使用且价格低廉,专为帮助农业领域的科学家而设计。该系统采用神经网络算法和图像处理技术对二十种草药进行识别。每个物种有100个样本通过该系统,识别精度为98.9%。最重要的是,该系统即使在干燥,湿润,撕裂或变形的情况下,也能够识别草药叶物种。实验证明了该方法在识别和分类不同草药种类中的效率和有效性。保留所有权利,Elsevier。

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