Using Texture Analyses and Statistical Classification for Detection Plant Leaf Diseases

Authors

  • Basim K.M.A Al-Windi Department of Computer Science, College of Science, Mustansiriyah University, Baghdad, Iraq.
  • Amel H. Abbas Department of Computer Science, College of Science, Mustansiriyah University, Baghdad, Iraq.
  • Mohammed Shakir Mahmood Ministry of Higher Education and Scientific Research, Scholarships and Cultural Relations Directorate, Baghdad, IRAQ.

DOI:

https://doi.org/10.23851/mjs.v32i5.1115

Keywords:

GLCM, Texture Analyses, HSV (Hue Saturation Value), Statistical Classification

Abstract

The proposed method is based on classifying 15 types of plant leaf disease. Hue saturation value was used to delete the background and the healthy areas to show only the affected area in the image. Texture analyses adopted in image features extractions from the R component &G component &B component and creating 3 components which are RG and RB and GB color of the RGB color space images of diseased leaves. Building image classifier using statistical method for classification.

References

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Published

2021-12-15

How to Cite

[1]
B. K. Al-Windi, A. H. Abbas, and M. S. Mahmood, “Using Texture Analyses and Statistical Classification for Detection Plant Leaf Diseases”, MJS, vol. 32, no. 5, pp. 1–4, Dec. 2021.