Parameter Optimization of Stereo Matching for Plant Height Estimation

Abstract

Plant height is one of the most important components in plant growth monitoring. In recent years, the development of stereo imaging techniques and hardware allows for precise measurement of 3D structure of an object. However, in order to monitor plant growth at multiple points in time, it is necessary to construct an affordable system from a practical viewpoint in agriculture. Therefore, in this study, we focus on parameter optimization in parallax estimation to achieve highly accurate plant height measurement even with inexpensive hardware. In particular, this study applies two optimization methods, namely Bayesian optimization and a Genetic algorithm, to several parameters of the basic algorithm for disparity estimation. The results of this study show that the optimization method can improve the accuracy of plant height measurement with inexpensive devices.