Detection of unhealthy region of plant leaves and classification of plant leaf diseases using texture features

Authors

  • S. Arivazhagan Department of Electronics and Communication Engineering, Mepco Schlenk Engineering College, Sivakasi Tamilnadu, 626 005, India
  • R. Newlin Shebiah Department of Electronics and Communication Engineering, Mepco Schlenk Engineering College, Sivakasi Tamilnadu, 626 005, India
  • S. Ananthi Department of Electronics and Communication Engineering, Mepco Schlenk Engineering College, Sivakasi Tamilnadu, 626 005, India
  • S. Vishnu Varthini Department of Electronics and Communication Engineering, Mepco Schlenk Engineering College, Sivakasi Tamilnadu, 626 005, India

Abstract

Plant diseases have turned into a dilemma as it can cause significant reduction in both quality and quantity of agricultural products.  Automatic detection of plant diseases is an essential research topic as it may prove benefits in monitoring large fields of crops, and thus automatically detect the symptoms of diseases as soon as they appear on plant leaves.  The proposed system is a software solution for automatic detection and classification of plant leaf diseases.  The developed processing scheme consists of four main steps, first a color transformation structure for the input RGB image is created, then the green pixels are masked and removed using specific threshold value followed by segmentation process, the texture statistics are computed for the useful segments, finally the extracted features are passed through the classifier.  The proposed algorithm’s efficiency can successfully detect and classify the examined diseases with an accuracy of 94%.  Experimental results on a database of about 500 plant leaves confirm the robustness of the proposed approach.

 

Keywords: HSI, color co-occurrence matrix, texture, SVM, plant leaf diseases

Downloads

Published

2013-04-09

Issue

Vol. 15 No. 1 (2013): CIGR Journal

Section

VII-Information Systems