Abstract
Rice is the staple food in the southern parts of India. Its yield directly affects the economy of the state. Rice blast, brown spot, and bacterial blight are the major diseases that can be seen in the leaves of the paddy crop which also greatly affect their productivity. The farmers, with limited knowledge of the disease, add irrelevant pesticides in inappropriate quantities, which not only diminishes the quality of the crop but also leads to the degradation of the soil quality and other environmental degradations. The proposed method uses image processing techniques to detect what disease has affected the leaves and also calculate the severity of the infection by calculating the percentage of the affected area, which can be used in controlling the excessive use of pesticides. The above mentioned diseases are the predominant diseases occurring in paddy crops among other diseases that vastly affect the yield and in turn affect the economic income of the farmers.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Islam R, Rafiqul Islam M (2015) An image processing technique to calculate percentage of disease affected pixels of paddy leaf. Int J Comput Appl (0975–8887) 123(12) 2015
Mukherjee M, Pal T, Samanta D (2012) Damaged paddy leaf detection using image processing. J Glob Res Comput Sci 3(10)
Narmadha RP, Arulvadivu G (2017) Detection and measurement of paddy leaf disease symptoms using image processing. In: International conference on computer communication and informatics (ICCCI-2017), Coimbatore, India
Abadi NE, Sadi LA (2013) Automatic detection and recognize different shapes in an image. IJCSI Int J Comput Sci Issues 10(6, no 1)
Veni S, Narayanankutty KA (2014) Vision-based hexagonal image processing using Hex-Gabor. Signal Image Video Process 8:317–326
Smita N, Niket A (2013) Advances in image processing for detection of plant diseases. Int J Appl Innov Eng Manage (IJAIEM) 2(11)
Parthasarathi V, Surya M, Akshay B, Murali Siva K, Shriram Vasudevan K (2015) Smart control of traffic signal system using image processing. Indian J Sci Technol Indian Soc Educ Environ 8(16) (2015)
Srunitha K, Bharathi D (2018) Mango leaf unhealthy region detection and classification. Lecture Notes Comput Vis Biomech 28:422–436
Anand R, Veni S, Aravinth J (2016) An application of image processing techniques for detection of diseases on brinjal leaves using K-means clustering method. In: IEEE international conference on circuit, power and computing technologies, ICCPCT
Nidhis, AD, Venkata Pardhu CN, Charishma Reddy K, Deepa K (2018) Smart crop health diagnosis and treatment unit powered by green fuel. J Green Eng 8(3):389–410
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Nidhis, A.D., Pardhu, C.N.V., Reddy, K.C., Deepa, K. (2019). Cluster Based Paddy Leaf Disease Detection, Classification and Diagnosis in Crop Health Monitoring Unit. In: Peter, J., Fernandes, S., Eduardo Thomaz, C., Viriri, S. (eds) Computer Aided Intervention and Diagnostics in Clinical and Medical Images. Lecture Notes in Computational Vision and Biomechanics, vol 31. Springer, Cham. https://doi.org/10.1007/978-3-030-04061-1_29
Download citation
DOI: https://doi.org/10.1007/978-3-030-04061-1_29
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-04060-4
Online ISBN: 978-3-030-04061-1
eBook Packages: EngineeringEngineering (R0)