DEVELOPMENT OF A HIGH-PERFORMANCE METHOD FOR DETERMINING THE GEOMETRIC PARAMETERS OF OBJECTS IN THE IMAGE
Keywords:
Contactless measurement methods, geometric parameters of objects, Canny detector, Hough algorithm, YOLOv5, mathematical morphology, convolutional neural networksAbstract
Currently, the development of various process automation systems is becoming more widely
used every day in various fields and industries, the task of developing software methods for the
corresponding automated systems remains urgent. One of the industries where the use and application
of process automation systems is in demand is the field of non-contact measurement of objects
and their parameters. As an example, the task of determining the geometric parameters of
round timber stacked was chosen. In this regard, in this paper, methods were proposed for determining
the geometric parameters of objects based on mathematical morphology operations, organized
using the Canny detector and the Hough algorithm, and a method using a neural network
approach based on the architecture of the YOLOv5 convolutional neural network. As a result of
the conducted experimental studies, for the organization of which specially 3d-printed models of
logs were used, it was found that the method based on the use of neural networks is more accurate
than the method based on mathematical morphology. When solving the problem of counting the
number of objects in the image, using the method based on the neural network approach, all objects
located in the image were determined, whereas the method using mathematical morphology operations was able to determine only 13 of the 16 logs located, and I identified one false object,
as a result of which the result error was about 19% for an image obtained from the Internet. When
conducting an experiment on manufactured cylinder models, the method based on mathematical
morphology operations showed unsatisfactory results. Another advantage of the method based on
the neural network approach is the possibility of calculating the area of the ends of logs in the
image and determining the volume of each of the logs located in the stack, as well as the total total
volume of the entire pack of measured round timber.
