SEGMENTATION OF 3D POINT CLOUDS DATA TO ANALYZE ENVIRONMENTAL ADAPTATIONS IN SORGHUM

Annotation: Climate change and varied precipitation patterns are threatening the sustainability of food production in India. Our challenge is to develop novel technologies that allow crop production to be observed or analyzed in the face of declining water availability. International Crops Research Institute for the Semi-Arid Tropics ( ICRISAT) is one of the leading institutes that pave the way for further progress in this area by using up-to-date technologies. The imaging platform they use produces the opportunity for analyzing critical features for drought adaptation and harnesses crop genetics for the breeding of improved varieties. This study introduces the software tool which facilitates the analysis of the 3D point clouds data collected by the ICRISAT. Thanks to the software tool developed, the 3D crop data segments from the tray, soil and the noise data. When the outputs are examined in detail, it is clearly seen that the separation process has been carried out successfully. Thus, the first step to produce more consistent data analysis results by using state of art machine learning algorithms has been fulfilled.