This paper is published in Volume-3, Issue-4, 2017
Area
AIET, Lucknow
Author
Arifa Khan
Co-authors
Manmohan Singh Yadav, Dr. Shafeeq Ahmad
Org/Univ
AIET, Lucknow, India
Pub. Date
31 July, 2017
Paper ID
V3I4-1267
Publisher
Keywords
Sugarcane, Leaf Disease Detection, Computer Vision, Segmentation, Image Processing.

Citationsacebook

IEEE
Arifa Khan, Manmohan Singh Yadav, Dr. Shafeeq Ahmad. Image Processing Based Disease Detection for Sugarcane Leaves, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Arifa Khan, Manmohan Singh Yadav, Dr. Shafeeq Ahmad (2017). Image Processing Based Disease Detection for Sugarcane Leaves. International Journal of Advance Research, Ideas and Innovations in Technology, 3(4) www.IJARIIT.com.

MLA
Arifa Khan, Manmohan Singh Yadav, Dr. Shafeeq Ahmad. "Image Processing Based Disease Detection for Sugarcane Leaves." International Journal of Advance Research, Ideas and Innovations in Technology 3.4 (2017). www.IJARIIT.com.

Abstract

Sugarcane is one of the most important crop in India. Indian sugar industry is the second largest agro based industry, next only to the textiles. But, being long durational crop, sugarcane is prone to the number of disease caused by pathogens viz. fungi, bacteria, viruses and phytoplasmas like organisms. Image processing techniques has been proved to be changing the scenario of agriculture in India with a number of research and applications like automatic disease detection, drone based pesticides and fertilizer dispensing, estimation of yield, vegetative growth, fruit sorting etc. This research is carried out to study effectiveness of Image Processing and computer vision techniques for detection of disease in sugarcane plants by observing the leaves. Few major diseases in sugarcane plant like red rot, mosaic and leaf scald have been studied and detection algorithm for the same has been implemented in this research work.
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