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A comprehensive study of feature extraction techniques for plant leaf disease detection

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Abstract

Agriculture has been the most primary source of the livelihood of man for thousands of years. Even today, it provides subsistence to about 50% of the world population. Plant diseases are the serious cause of big losses to crop production every year worldwide. It is necessary to keep the plants healthy at various stages of their growth/development to deal with the financial losses from plant diseases. Symptoms of infections are visible mainly at plant leaves; thus leaves are commonly used to detect and identify the diseases. Detecting the disease through visual observation is itself a challenging task and requires a lot of human expertise. Image processing techniques along with computational intelligence or soft computing techniques can be used to provide a better assistance for disease detection to the farmers. A disease in plants can be detected based on its symptoms extracted in the form of features. Feature extraction techniques thus play a vital role in such systems. The paper emphasizes on the review of hand-crafted and deep learning based feature extraction with their merits and demerits. It provides a comprehensive discussion on a variety of image features such as color, texture, and shape for various disorders in different cultures.

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  1. Department of Computer Science, Gurukula Kangri Vishwavidyalaya, Haridwar, Uttarakhand, 249404, India

    Vibhor Kumar Vishnoi & Krishan Kumar

  2. Department of Computer Science & IT, MJP Rohilkhand University, Bareilly, Uttar Pradesh, 243006, India

    Brajesh Kumar

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Correspondence to Vibhor Kumar Vishnoi.

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Appendices

Appendix 1

1.1 Summary of research works based on texture features

The research efforts for plant disease detection based on texture features are summarized in Table 3.

Table 3 Summary of research work based on texture feature extraction techniques and various texture features
Full size table

Appendix 2

1.1 Summary of plant disease detection research based on color features

The color features based research on plant disease detection and diagnosis is summarized in Table 4.

Table 4 Summary of research work based on color feature extraction techniques and various color features
Full size table

Appendix 3

1.1 Summary of plant disease detection research on shape features

The shape features based research on plant disease detection and diagnosis is summarized in Table 5.

Table 5 Summary of research work based on shape feature extraction
Full size table

Appendix 4

1.1 Summary of plant disease detection research on combined features

The combinations of texture, color, and shape features based research on plant disease detection and diagnosis is summarized in Table 6.

Table 6 Summary of research work based on combinations of feature extraction techniques and combined features
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Vishnoi, V.K., Kumar, K. & Kumar, B. A comprehensive study of feature extraction techniques for plant leaf disease detection. Multimed Tools Appl 81, 367–419 (2022). https://doi.org/10.1007/s11042-021-11375-0

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