Influence of Graphical Representation Type on Tessellated Geometry Classification

Maciej Majchrzak; Katarzyna Marciniak-Lukasiak; Mateusz Jakubowski; Piotr Lukasiak

doi:10.2478/fcds-2026-0004

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Influence of Graphical Representation Type on Tessellated Geometry Classification

Foundations of Computing and Decision Sciences

Volume 51 (2026): Issue 1 (March 2026)

By: Maciej Majchrzak, Katarzyna Marciniak-Lukasiak, Mateusz Jakubowski and Piotr Lukasiak

Open Access

|Mar 2026

Abstract

This research investigates the impact of graphical representation on the accuracy of three-dimensional shape classification. 3D models, both scanned and modeled, are used in engineering, computer graphics and scientific data visualization. Various approaches are adopted in these fields to visually represent 3D geometry, utilizing solutions such as OpenGL and Direct3D, each with its distinct goal of achieving either real-time manipulation or photorealism. The purpose of this research was to determine the most effective graphical representation for categorizing mechanical components with a high degree of geometric similarity, such as beams and rods. The study examined various image representations and their combinations, obtained through the adjustment of rendering parameters and image compositing. In an effort to improve classification accuracy, novel techniques for addressing image recognition issues were developed and tested against commonly used image representation methods. This innovative approach proposed in the paper led to a 48% reduction in classification errors.

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Articles in this issue

DOI: https://doi.org/10.2478/fcds-2026-0004 | Journal eISSN: 2300-3405 | Journal ISSN: 0867-6356

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Language: English

Page range: 111 - 138

Submitted on: Sep 5, 2025

Accepted on: Feb 24, 2026

Published on: Mar 17, 2026

Published by: Poznan University of Technology

In partnership with: Paradigm Publishing Services

Publication frequency: 4 issues per year

Keywords:

3D scanning,

Image classification,

Convolutional neural networks,

Rendering (computer graphics),

Computer aided design,

machine learning

Related subjects:

Computer sciences,

Artificial intelligence,

Software development

© 2026 Maciej Majchrzak, Katarzyna Marciniak-Lukasiak, Mateusz Jakubowski, Piotr Lukasiak, published by Poznan University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Volume 51 (2026): Issue 1 (March 2026)