Verification of image processing methods using digital cameras for rice growth diagnosis

Abstract

Vegetation indices derived from digital camera images have been shown to be useful for rice growth diagnosis in previous research. However, various image processing methods were proposed for calculation of vegetation indices, and they were not standardized. Hence, we compared several image processing methods to identify the suitable method for evaluation of rice leaf area index and above ground biomass using RGB images and false color images. Vegetation indices were calculated with different image processing method, and prediction accuracy for rice growth from the vegetation indices were evaluated. As a result, color and brightness correction improved relationships between rice growth and vegetation indices but segmenting the rice plant area and reduction of gamma correction were not necessary. Through this study, the findings showed the possibility of rice growth diagnosis using aerial images taken by unmanned aerial vehicles.