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Automatic Agricultural Leaves Recognition System

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 201)

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.

Keywords

  • Principal component analysis
  • Support vector machine
  • Leaf segmentation
  • Leaf classification

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© 2013 Springer India

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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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  • Publisher Name: Springer, India

  • Print ISBN: 978-81-322-1037-5

  • Online ISBN: 978-81-322-1038-2

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