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Detecting Healthiness of Leaves Using Texture Features

  • Srishti Shetty
  • Zulaikha Lateef
  • Sparsha Pole
  • Vidyadevi G. Biradar
  • S. BrundaEmail author
  • H. A. Sanjay
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 906)

Abstract

Agriculture is the dominant sector of our economy and contributes in various ways but the yield in the productivity leads to a significant reduction in the farmer’s income. Monitoring crop health is important to increase the quality and quantity of the yield. But this requires manually monitoring the crops and also expertise in the field. Hence, automatic disease detection using image texture features is used for ease and to detect the disease at an early stage. The proposed methodology for the project is to design and implement the algorithm on two sets of databases: firstly, a locally generated leaf database which contains images of leaves and secondly, a standard database which is a common test database. The basic steps for crop disease detection include image acquisition, image preprocessing, image segmentation, feature extraction, and classification using image processing techniques. The acquired leaf images are preprocessed by removing undesired distortion and noise, and then, the processed image is further subjected to K-means-based segmentation. The segmented image is further analyzed using Haar wavelet transform and GLCM based on its texture by extracting feature vector. SVM is used for classification of image. Thus, the presence of diseases in leaf is identified along with all the features values of the leaf. It also calculates the accuracy rate of the prediction made by the system.

Keywords

Image processing Gray-level co-occurrence matrix Support vector machine-nearest neighbor Haar wavelet K-means 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Srishti Shetty
    • 1
  • Zulaikha Lateef
    • 1
  • Sparsha Pole
    • 1
  • Vidyadevi G. Biradar
    • 1
  • S. Brunda
    • 1
    Email author
  • H. A. Sanjay
    • 1
  1. 1.Department of ISENMITBangaloreIndia

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