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Image Processing Based Approach for Diseases Detection and Diagnosis on Cotton Plant Leaf

  • Khushal Khairnar
  • Nitin Goje
Conference paper

Abstract

Diseases are decreasing the production of the plants. At present, farmers are identifying and diagnosing the diseases and monitoring the health of plants with their own knowledge and experience. Naked eye observation by farmers and experiments on big plantation area can not be possible each time and it can be expensive too. Accurate identification of visually observed diseases, symptoms and controls have not been studied yet. Therefore fast automatic, economical and accurate system is essential to research leaf disease detection of plants. The proposed system is based on image processing, the infected cotton plant leaf image is first segmented using the K-means algorithm. Then Color and texture features have been extracted from the segmented image. Disease detection through feature classification will be done by support vector machine. It could provide significant information about fertilizers, symptoms, prediction, and control of the diseases.

Keywords

Image preprocessing Diseases diagnosis K-means clustering Feature extraction Segmentation Support vector machine 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Khushal Khairnar
    • 1
  • Nitin Goje
    • 2
  1. 1.Computer Science and EngineeringSandip UniversityNashikIndia
  2. 2.School of Computer and ApplicationsSandip UniversityNashikIndia

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