The Different Techniques for Detection of Plant Leaves Diseases

  • Akshay Kumar
  • Ranvijay Singh
  • Shashidhara
  • Neha
  • Thirukrishna
DOI: https://doi.org/10.36079/lamintang.ijai-0901.342
Keywords: Disease Identification, Feature Extraction, Image Processing, Leaf Disease

Abstract

As we know that Plant disease detection is an interesting field. Plants are the way to live. In our daily life we are completely dependent on plants. There by plants should be taken care. In most of the studies it is been shown that quality of agricultural products shall be reduced due to various components. The plant diseases are such as bacteria, viruses and fungi. The disease in plant leaf restricts the growth of the plant and also destroys its yield. Every time there is the need of expert to identify plant diseases but manual identification is expensive and also time consuming. So, automatic methods are necessary for detection of disease. Through this paper, we have presented a survey on the different methods of plant leaf disease detection.

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Author Biographies

Akshay Kumar

Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management. Bangalore, India.

Ranvijay Singh

Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management. Bangalore, India.

Shashidhara

Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management. Bangalore, India.

Neha

Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management. Bangalore, India.

Thirukrishna

Department of Information Science and Engineering, Dayananda Sagar Academy of Technology and Management. Bangalore, India.

This is an open access article, licensed under CC-BY-SA

Creative Commons License
Published
        Views : 215
2022-06-07
    Downloads : 199
How to Cite
[1]
A. Kumar, R. Singh, Shashidhara, Neha, and Thirukrishna, “The Different Techniques for Detection of Plant Leaves Diseases”, International Journal of Artificial Intelligence, vol. 9, no. 1, pp. 1-7, Jun. 2022.
Issue
Vol 9 No 1: June 2022
Section
Articles

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