Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/19
Title: A Review on Plant Disease Detection Using Image Processing
Authors: Bharate, Anil A
Shirdhonkar, M. S.
Keywords: Classification; Feature extraction; Image processing; Plant disease; Symptom
Issue Date: 2018
Publisher: IEEE
Series/Report no.: CFP17M19-ART,;
Abstract: India is the agriculture based country, since it contributes 7.68 percent of total global agricultural output. In India, agricultural sector contributes about seventeen percentage of total Indian gross domestic product (GDP). Effective growth and improved yield of plants are necessary for increment of farmer’s profit and economy of India. For this purpose farmers need domain experts for manual monitoring of plants. But manual monitoring will not give satisfactory result all the time. Moreover, domain experts are not available at all regions and are expensive as farmers have to pay fees including travelling charges. Hence, it requires developing an efficient smart farming technique which will help for better yield and growth with less human efforts. In this paper, we provide a review on methods developed by various researchers for detection of diseases in plants, in the field of image processing. It includes research in disease detection of plants such as apple, grapes, pepper, pomegranate, tomato etc.
URI: http://hdl.handle.net/123456789/19
ISBN: 978-1-5386-1959-9
Appears in Collections:F P

Files in This Item:
File Description SizeFormat 
bharate2017.pdf496.59 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.