Plant leaf disease detection using gabor wavelet transform

Authors:
Shitala Prasad;Piyush Kumar;Ranjay Hazra;Ajay Kumar
Affiliations:
Department of Electronics and Computer Engineering, IIT Roorkee, India;Department of Information Technology, IIIT Allahabad, India;Department of Electronics and Computer Engineering, IIT Roorkee, India;Department of Electronics and Instrumentation, UCER Allahabad, India
Venue:
SEMCCO'12 Proceedings of the Third international conference on Swarm, Evolutionary, and Memetic Computing
Year:
2012

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Abstract

This paper explores a new dimension of pattern recognition to detect crop diseases based on Gabor Wavelet Transform. The first proposed plant biometric system consist three modules: (1) spot detection using histogram based segmentation, (2) feature extraction using GWT and (3) feature matching with advance machine learning algorithm, SVM. The experimental results on different disease dataset shows that the GWT is effective and robust algorithm for plant disease detection. The accuracy is around 89% in all circumstances. The developed system is very helpful in biology and botanical studies and also used to guide and make aware the Indian farmers about the crop diseases and their natural and chemical controls to improve the production rate.