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Tracing and Recognition of Medicinal Herbs in Marunthuvazh Malai at the Western Ghats Through Feature Extraction


Affiliations
1 Department of Information Technology, University College of Engineering, Nagercoil, India., India
2 Department of Mechanical Engineering University College of Engineering, Nagercoil, India., India
     

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The identification and classification of the herbs using the naked eye is difficult in forest or mountain areas like Marunthuvazh Malai of Kanyakumari district. The difficulties arise because of the variations in the crops identified are inaccurate. Mostly the manual prediction is taken place in those areas which require high expertise and more human resources. In this work both plant identification and tracking system based on fuzzy empowered Hybrid artificial neural networks (FHANN) are proposed. Here the input is taken from the video signals taken by the drone camera. The input video signals are converted into images. The fuzzy logic along with the HANN is used for the classification of the specific herbs from the set of plants. Some of the herbs included in the analysis are Parsley, Dill, Oregano, Chervil, Stevia, Basil, Catnip, Fennel and Lemon Grass. This approach used artificial neural networks (ANN) in combination with the K-Nearest neighbor (KNN) as the hybrid model for the herb prediction and classification in association with the fuzzy logic. The Linear Discriminant Analysis (LDA) and Convolutional Autoencoder are used as a hybrid model for the extraction of the feature from the obtained images. This approach considers various shapes, color features, and textures specifically representing the specific herbs. The experimental results show that the proposed model provides better results in the identification and classification of the various medicinal herbs.

Keywords

Artificial Neural Networks, K-Nearest Neighbour, Linear Discriminant Analysis, Convolutional Auto Encoder.
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  • Tracing and Recognition of Medicinal Herbs in Marunthuvazh Malai at the Western Ghats Through Feature Extraction

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Authors

T. Sahila
Department of Information Technology, University College of Engineering, Nagercoil, India., India
A. Radhakrishnan
Department of Information Technology, University College of Engineering, Nagercoil, India., India
V.A. Nagarajan
Department of Mechanical Engineering University College of Engineering, Nagercoil, India., India

Abstract


The identification and classification of the herbs using the naked eye is difficult in forest or mountain areas like Marunthuvazh Malai of Kanyakumari district. The difficulties arise because of the variations in the crops identified are inaccurate. Mostly the manual prediction is taken place in those areas which require high expertise and more human resources. In this work both plant identification and tracking system based on fuzzy empowered Hybrid artificial neural networks (FHANN) are proposed. Here the input is taken from the video signals taken by the drone camera. The input video signals are converted into images. The fuzzy logic along with the HANN is used for the classification of the specific herbs from the set of plants. Some of the herbs included in the analysis are Parsley, Dill, Oregano, Chervil, Stevia, Basil, Catnip, Fennel and Lemon Grass. This approach used artificial neural networks (ANN) in combination with the K-Nearest neighbor (KNN) as the hybrid model for the herb prediction and classification in association with the fuzzy logic. The Linear Discriminant Analysis (LDA) and Convolutional Autoencoder are used as a hybrid model for the extraction of the feature from the obtained images. This approach considers various shapes, color features, and textures specifically representing the specific herbs. The experimental results show that the proposed model provides better results in the identification and classification of the various medicinal herbs.

Keywords


Artificial Neural Networks, K-Nearest Neighbour, Linear Discriminant Analysis, Convolutional Auto Encoder.

References