Application of Image Processing Techniques and Artificial Neural Network for Detection of Diseases on Brinjal Leaf

Abstract

The plant diseases cause damage and monetary losses in crops. The farmers monitor the crops in the field at regular intervals in order to detect various diseases. Instead of manual diagnosis, computers have been used to provide automatic detection and classification of different types of diseases. In this paper, the lesion areas affected by diseases are segmented. Further, discrete wavelet transform based image fusion technique is used to improve the imaging quality reducing redundancy. The colour, texture and structural based features of the fused images are extracted and given as an input to the ANN for classification which provides better performance.

Keywords:

• Artificial neural networks
• Cascaded feed forward neural network
• Discrete wavelet transform
• Image fusion
• Structural features
• Texture features

Acknowledgements

I would express my sincere gratitude to my advisor for the continuous support in my research work. I would like to thank my family and colleague for their excellent support when I was writing this article.

Additional information

Notes on contributors

S. Abisha

S Abisha received a BE degree in electronics and communication engineering in 2012 and ME degree in communication systems in 2014. Presently, she is pursuing PhD degree in Anna University. Corresponding author. Email: [email protected]

T. Jayasree

T Jayasree, completed her BE degree from Barathidasan University, Trichy, in 1997 and ME from Govt College of Technology, Coimbatore, in 1999. She completed her PhD degree from Anna University Chennai in 2011 in the area of signal processing. She has more than 15 years of teaching experience. Presently, she is working as an assistant professor in the Department of ECE in Govt College of Engineering, Tirunelveli, Tamilnadu, India. She has published many papers in national and international journals and conferences. Her areas of interest is in signal processing applications in power quality, speech processing and biomedical signal processing. Email: [email protected]