Publication Type:

Conference Paper

Source:

Computer Aided Intervention and Diagnostics in Clinical and Medical Images, Springer International Publishing, Volume 31, Cham, p.281-291 (2019)

ISBN:

9783030040611

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.

Notes:

cited By 1

Cite this Research Publication

A. D. Nidhis, Pardhu, C. Naga Venka, K. Reddy, C., and Dr. K. Deepa, “Cluster Based Paddy Leaf Disease Detection, Classification and Diagnosis in Crop Health Monitoring Unit”, in Computer Aided Intervention and Diagnostics in Clinical and Medical Images, Cham, 2019, vol. 31, pp. 281-291.