The Image Analysis Algorithm for the Log Pile Photogrammetry Measurement

This paper is devoted to the investigation and development of the algorithm for the log pile photogrammetry measurement on the basis of abuts detection and calculation of their diameters. The algorithm of abuts contours detection and refinement relies on the modified radial symmetry object detection algorithm. The combination of the following methods is implemented at the further stages of the pile measurement algorithm: meanshift clustering, Delaunay triangulation, Boruvka's minimum spanning tree algorithm, watershed and Boykov-Kolmogorov graph cut algorithm. These methods were adapted to the specific of the given task. The testing of the resulting algorithm gives its TPR value at 96,2% which is much higher than other unsupervised training methods. The average error of the algorithm for the log pile photogrammetry measurement in comparison with manual measurement is less than 9.2%. It meets the requirements of the industry standards so the method of the log piles photogrammetry measurement using the developed algorithm can be successfully applied in the activity of forest enterprises. Key-Words: Log pile, Photogrammetry, Abut detection, Radial symmetry, Meanshift clustering, Graph cut, Watershed, Volume measurement