• PRABIRA KUMAR SETHY
• SHOUBHAGYALINA DASH
• NALINI KANTA BARPANDA
• AMIYA KUMAR RATH

Rice covers about 69% of the cultivated area and is the major crop, covering about 63% of the total area under food grains. It is the staple food of almost the entire population of Odisha. Therefore, the state economy is directly link with improvements in production and productivity of rice in this state. Almost 1.10 lakh acres of farmland across the state of Odisha affected due to brown plant hoppers year 2018-19. Therefore, it is necessity to quantifying the population density of rice brown plant hopper (RBPH) and make decisions for its treatment. Manually it is time-consuming and unreliable. Here we propose a methodology where a smartphone mounted in selfie stick used to capture planthopper images on rice stems and by application of image processing technique the population density of RBPH scaled. The methodology includes image enhancement, median filtering and k-means clustering for segmentation.

Rice planthopper; median filter; k-means clustering; image processing technique.

"A Novel Approach for Quantification of Population Density of Rice Brown Plant Hopper (RBPH) Using On-Field Images Based On Image Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.252-256, May-2019, Available :http://www.jetir.org/papers/JETIR1905539.pdf

"A Novel Approach for Quantification of Population Density of Rice Brown Plant Hopper (RBPH) Using On-Field Images Based On Image Processing", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp252-256, May-2019, Available at : http://www.jetir.org/papers/JETIR1905539.pdf