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Identification of Banana Disease Using Color and Texture Feature

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Recent Trends in Image Processing and Pattern Recognition (RTIP2R 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1381))

Abstract

Plant diseases have grown-up in agriculture to be an impasse as it can cause dwindling in both quantity and quality of farming yield. This work explains a simple and adept method used to recognize leaf diseases by applying digital image processing and machine learning technology. In this study 24 color feature, 12 shape and 4 texture features were obtained from images of four kinds of diseases like, Sigatoka, Panama Wilt, Bunchy Top and Banana Streak Virus diseases. Principal component analysis (PCA) was achieved for reducing dimensions in features extracted and k-nearest neighbour classifiers used to identify banana diseases. The finest result was obtained when image identification was conducted based on PCA with K-nearest neighbour classifier.

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Authors and Affiliations

  1. Smt.G.G. Khadse College, Muktainagar, India

    Vandana V. Chaudhari

  2. School of Computer Sciences, Kaviyatri Bahinabai Chaudhari, North Maharashtra University, Jalgaon, India

    Manoj P. Patil

Authors
  1. Vandana V. Chaudhari
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  2. Manoj P. Patil
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Corresponding authors

Correspondence to Vandana V. Chaudhari or Manoj P. Patil .

Editor information

Editors and Affiliations

  1. University of South Dakota, Vermillion, SD, USA

    K. C. Santosh

  2. Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, India

    Bharti Gawali

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Chaudhari, V.V., Patil, M.P. (2021). Identification of Banana Disease Using Color and Texture Feature. In: Santosh, K.C., Gawali, B. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2020. Communications in Computer and Information Science, vol 1381. Springer, Singapore. https://doi.org/10.1007/978-981-16-0493-5_21

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  • DOI: https://doi.org/10.1007/978-981-16-0493-5_21

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-0492-8

  • Online ISBN: 978-981-16-0493-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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