Robust texture based biomass estimation of small fronded floating aquatic plants using j-values

Abstract

This paper proposes a new method of estimation of the wet biomass of three floating aquatic plants, Spirodela polyrhiza, Lemna minor and Azolla pinnata. The method uses a homogeneity measure known as the J-value to detect the texture of the fronds of the plants from the uniform water surface. The proposed method is called J-value thresholding (JVT) and is highly accurate compared to the alternative green layer extraction (GLE). The average accuracy under normal illumination for the proposed method is 91.59% for Spirodela polyrhiza, 80.11% for Lemna minor and 77.4% for Azolla pinnata. Furthermore, it is robust to different illumination levels with the Pearson correlation coefficient of the estimates of different illumination levels being above 95%. When used to obtain the growth rate of each plant specie through linear regression, the result from the proposed method is highly consistent with the ground truth of the image.