Year: 2025
Type: article
Abstract: Purpose of research. The purpose of the research is to develop a generalized method for estimating the geometric parameters of an object from photographs in the absence of information about the a priori parameters of the object, as well as with the possibility of using digital cameras with various optical systems to produce images. Methods. To achieve this goal, a mathematical model of an optical system consisting of two digital cameras was developed. Then, by reducing this mathematical model to a single system of equations, a method was developed for calculating the coordinates of an object in an image, as well as the distance to it. Then the experimental verification of the obtained method was carried out. Results. The result of the work is a generalized method for estimating the geometric parameters of an object in the absence of information about the a priori parameters of the object using two images from digital cameras with different optical systems. An experimental verification of the accuracy of the developed method was performed when calculating the distance to an object using standard cameras with different lenses, which showed that this method allows estimating the geometric parameters of objects with an accuracy of 90% or higher, depending on the accuracy of measuring the technical parameters of the cameras. The sensitivity of the developed method to the values of the technical parameters of the digital cameras used was also evaluated. Conclusion. Experimental tests have shown that the developed method allows us to accurately estimate the distance to objects using images from two digital cameras, however, it requires high accuracy in measuring the technical parameters of the cameras used. As further ways of developing this method, it is possible to note the possibility of increasing the accuracy of measurements by adding nonlinear distortions (distortions) to the developed mathematical model.
Author: K. D. Konovalov
Institution: Russian Academy of Sciences
Language: English
Topic: Advanced Vision and Imaging
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4411243819