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Adaptive Neuro Fuzzy Inference System based Tea Leaf Disease Recognition using Color Wavelet Features

Mustain Billah, Mohammad Badrul Alam Miah, Abu Hanifa, Md. Ruhul Amin. Published in Fuzzy Systems.

Communications on Applied Electronics
Year of Publication: 2015
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Mustain Billah, Mohammad Badrul Alam Miah, Abu Hanifa, Md. Ruhul Amin

Mustain Billah, Mohammad Badrul Alam Miah, Abu Hanifa and Md. Ruhul Amin. Article: Adaptive Neuro Fuzzy Inference System based Tea Leaf Disease Recognition using Color Wavelet Features. Communications on Applied Electronics 3(5):1-4, November 2015. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

	author = {Mustain Billah and Mohammad Badrul Alam Miah and Abu Hanifa and Md. Ruhul Amin},
	title = {Article: Adaptive Neuro Fuzzy Inference System based Tea Leaf Disease Recognition using Color Wavelet Features},
	journal = {Communications on Applied Electronics},
	year = {2015},
	volume = {3},
	number = {5},
	pages = {1-4},
	month = {November},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}


Tea, a favourite bevarage in the world is made of tender new leaves of tea plant. So tea plantation is more concerned with tea leaf diseases. Infected leaves may be the source of disease for new leaves reducing the productivity of the plant. In order to reduce tea leaf disease, disease recognition is the initial step. Many techniques have been used for leaf recognition. In this paper, we have proposed a model for recognising tea leaf diseases, which uses color wavelet features and adaptive neuro fuzzy inference system (ANFIS). After processing the images, color wavelet features are extracted and provided to Adaptive Neuro Fuzzy Inference System (ANFIS) along with the disease types. This ANFIS based tea leaf disease recognition system using color wavelet features can recognise the disease of any new leaf image affected by disease accurately.


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Image processing, ANFIS, Tea leaf disease, disease recognition