Estimating the accuracy and time consumption of a mobile machine vision application in measuring timber stacks

Abstract

Trestima Stack is a mobile application innovated by Trestima Ltd. It is based on machine vision, which measures the volume of a timber stack from images taken by a smartphone or a tablet device. The aim of this study was to determine the accuracy (i.e. measurement difference) and effective measurement time consumption of the Trestima Stack application compared to a conventional stacked timber measurement method. Research data consisted of a total of 60 timber stacks, of which 32 were measured in terminal and intermediate yards and 28 at roadside landings. The control volumes of the stacks were measured in September 2016 – January 2017 at the Stora Enso Anjala, Imatra and Varkaus mills by hydrostatic weighting. The total control volume of pulpwood in the study was 11,957 m3 solid over the bark (m3). Across all study data, the accuracy of Trestima Stack averaged +2.7%. In large terminal yards, accuracy was better (+0.7%) than at smaller roadside landings (+4.5%), whereas with the conventional stacked timber measurement method, the measurement accuracy was at a similar level in terminal yards (−4.8%) as at roadside landings (−4.9%). There was a statistically significant difference between the measurement methods used in measurement accuracy. The most common reason for inaccuracy with the Trestima Stack application was empty space in the final image framing around the stack. The average effective total measurement time consumption with Trestima Stack was 10.6 s/m3, while it was 13.7 s/m3 with the conventional stacked timber measurement method. For both measurement methods, there was a statistically significant negative correlation between the stack size and the volume-based effective total measurement time consumption. On the basis of this study, the Trestima Stack application can be recommended for inventorying timber stacks at the roadside landings, particularly when the stacks measured consist of several measurement batches.