| Hi-index | 0.00 |
In this work, we propose a preliminary study on objective approaches in evaluating the synthesized 3D plants from the given image data. Two measures, in a general name of "Resemblance Index (RI)," are defined and investigated based on the normalized mutual information (RINI), and coincident-bit-counting criterion (RICBC), respectively. We propose a strategy of hierarchical evaluations on different attributes of objects. In this study, we only consider the geometrical and crown distribution attributes. The numerical investigations confirm the approach to be useful for a fast evaluation of 3D reconstructed plants/trees from image data. Discussions are given about the two measures based on the numerical examples.