DETECTION OF DISEASED LEAF USING IMAGE PROCESSING TECHNIQUE

Authors

  • J.HEMA DEVI Asst.Prof, Department, Of Electronics and Communication Engineering
  • M.MERCY THERESA Student, Department Of Electronics and Communication Engineering, JEPPIAAR SRR Engineering College, Padur, Chennai- 603 103.
  • D.OVIYA Student, Department Of Electronics and Communication Engineering, JEPPIAAR SRR Engineering College, Padur, Chennai- 603 103

Keywords:

SIFT(scale invariant feature transform), ANN (Artificial neural network)

Abstract

Nowadays crops are damaged due to many types of diseases. Plant diseases have turned into a dilemma as it
can cause significant reduction in both quality and quantity of agricultural products. The developed scheme consists of
four steps likely, to create a colour transformation structure for the input RGB image followed by masking of green
pixels and its removal using threshold value which is then followed by segmentation process. The segmentation process
is achieved by Mumford shah algorithm. The feature extraction is achieved by (scale invariant feature transform) SIFT
algorithm. Finally the extracted features are passed to the classifier using (Artificial neural network) ANN algorithm.
Classifier using ANN algorithm is developed to classify the leaf according to their growth and colour change. Thus the
classifier is used for classifying the disease. This technique is a solution for automatic detection of leaf diseases using
growth, size and colour change

Published

2017-04-25

How to Cite

J.HEMA DEVI, M.MERCY THERESA, & D.OVIYA. (2017). DETECTION OF DISEASED LEAF USING IMAGE PROCESSING TECHNIQUE. International Journal of Advance Engineering and Research Development (IJAERD), 4(4), 1–6. Retrieved from https://ijaerd.com/index.php/IJAERD/article/view/2433