THE METHOD OF AUTOMATED PARAMETRIC TREE IDENTIFICATION
The author has developed a new method for automatic detection and parametric identification of trees in technological field of cut-to-length selective felling process, in which the qualification of an operator of the logging machine is the determining factor. The key stages of work include quantifying the number of trees on the felling site by analyzing the stereoscopic image of the area in front of the logging machine using the stereoscopic parallax method; calculation of taxation indicators (diameter, shape factor and stem height within the operating area of the harvester); identification of trees in the operating area for selective logging by means of a fuzzy logic solver based on the retrieved data and displaying on an operator’s screen the tree designated for felling with maximum probability. The method is based on the combination of the optical image of the surrounding and the image obtained from the depth of field using the means of a machine vision system. The selected objects are recognized using the proposed method based on the analysis of a vector silhouette. Typical contours for various tree silhouettes were obtained. The analysis of the results indicates a high degree of distinguishability of trees by the shape of their crown contour. Thus, the results of calculating the moduli of mutual normalized scalar products of the contours do not exceed the value of 0.5 at a single maximum level, when the two contours are identical. It has been established that a good distinction in terms of the separation of deciduous and coniferous trees is given by such an indicator as the form factor. Using analytical methods, the centres of gravity of trees of various species have been determined. Using the developed method of automatic recognition of tree species the author has developed a new method of automated assignment for felling. It has been experimentally established that the choice of trees assigned for felling based on the developed method and on inventory decision of a working plan officer coincides in 76 % cases, which corresponds to a high degree of consistency and makes the method applicable in real conditions of felling automation.