Abstract
India is an agricultural country where large number of human beings are involved in cropping different plants for their living. But these plants may be affected by different diseases which are to be handled by the farmers within time to increase their productivity. An automatic plant disease identification system can be helpful for the farmers to identify the disease and their cures within time. Most of these diseases can be identified using the leaves of the plants. Therefore, an automatic classification of leaves would be the prior step for disease identification system. The leaf recognition system is a complex task due to the presence of large variations in the leaves. Therefore, this paper proposes a novel methodology for classification of agricultural leaves into their respective class based on principal component analysis (PCA) and support vector machine (SVM). The results show that the proposed method is accurate and fast enough to classify the leaves.
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Meenakshi, Puja, D., Saraswat, M., Arya, K. (2013). Automatic Agricultural Leaves Recognition System. In: Bansal, J., Singh, P., Deep, K., Pant, M., Nagar, A. (eds) Proceedings of Seventh International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2012). Advances in Intelligent Systems and Computing, vol 201. Springer, India. https://doi.org/10.1007/978-81-322-1038-2_11
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DOI: https://doi.org/10.1007/978-81-322-1038-2_11
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