Disease detection on plant leaf using K-means segmentation with fuzzy logic SVM algorithm

https://doi.org/10.53730/ijhs.v6nS2.6127

Authors

  • M. Sowmya Ph.D. Research Scholar, Department of Computer Science, Shri Nehru Maha Vidhyala College of arts and sciences, Coimbatore, Tamil Nadu, India
  • Bojan Subramani Principal & Associate Professor, Department of Computer Science, Shri Nehru MahaVidhyala College of arts and sciences, Coimbatore, Tamil Nadu, India

Keywords:

K-means, fuzzy logic, support vector machine, segmentation, classification

Abstract

Detection of plant diseases requisite at its early stage to manage the large crop field. In plants existence of diseases result reduced yields of crops and therefore it is imperative to identify at its early stage. Leaf is the main part where the diseases symptoms are shown in the initial stage itself. Image processing techniques are used at the computing part whereas in this research a hybrid KMFLs (K-Means Fuzzy logics) and  SVMs (Support Vector Machines) are implemented to identify and categorize diseased plants based on leaf disease grades. This work’s proposed method is implemented by examining images of leaves for diseases including Alternaria alternates, Anthracnoses, Bacterial blights and Cercospora leaf spots. The input leaf image features are extracted which are subsequently used for categorizations into classes.

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References

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Published

16-04-2022

How to Cite

Sowmya, M., & Subramani, B. (2022). Disease detection on plant leaf using K-means segmentation with fuzzy logic SVM algorithm. International Journal of Health Sciences, 6(S2), 4749–4756. https://doi.org/10.53730/ijhs.v6nS2.6127

Issue

Section

Peer Review Articles