ANALYSIS OF PROCEDURAL AND FRACTAL METHODS FOR SYNTHESIZING TEXTURES OF NATURAL MATERIALS
DOI:
https://doi.org/10.5281/zenodo.23406884Abstract
This article examines procedural and fractal methods for the computer-based synthesis of natural material textures, including wood, stone, and fabric. The study explores mathematically grounded approaches to procedural texture generation, noise functions, techniques for constructing multiscale structures, and the potential of fractal models to represent the characteristics of natural surfaces. Based on a review of existing research, the distinctive features, advantages, and limitations of these methods are qualitatively compared. The analysis highlights the need to develop a parameter-controlled texture synthesis method that accounts for the structural characteristics of natural materials. The study is theoretical and analytical in nature and does not claim to demonstrate the experimental effectiveness of a newly developed algorithm.Keywords
texture synthesis, procedural modeling, fractal models, natural materials, wood textures, stone textures, fabric textures, noise functions, computer graphicsReferences
1. Akl, A., Yaacoub, C., & Donias, M. (2018). Da Costa J.-P., Germain C. A survey of exemplar-based texture synthesis methods. Computer Vision and Image Understanding, 172, 12–24. https://doi.org/10.1016/j
2. Barnsley, M. F. (1993). Fractals Everywhere / M.F. Barnsley.
3. Dong, J., Liu, J., Yao, K., Chantler, M., Qi, L., Yu, H., & Jian, M. (2020). Survey of procedural methods for two-dimensional texture generation. Sensors, 20(4). https://doi.org/10.3390/s20041135
4. Ebert, D. S., Musgrave, F. K., Peachey, D., Perlin, K., & Worley, S. (2003). Texturing and Modeling: A Procedural Approach / D.S. Ebert [et al.].
5. Efros, A. A., & Leung, T. K. (1999). Texture synthesis by non-parametric sampling. Proceedings of the Seventh IEEE International Conference on Computer Vision (ICCV), 1033–1038. https://doi.org/10.1109/
6. Haralick, R. M., Shanmugam, K., & Dinstein, I. (1973). Textural features for image classification. IEEE Transactions on Systems, Man, and Cybernetics, (6), 610–621. https://doi.org/10.1109/
7. Heeger, D. J., & Bergen, J. R. (1995). Pyramid-based texture analysis/synthesis. Proceedings of SIGGRAPH ‘95, 229–238. https://doi.org/10.1145/218380.218446
8. Liu, A. J., Dong, Z., Hašan, M., & Marschner, S. (2016). Simulating the structure and texture of solid wood. ACM Transactions on Graphics, 35(6), 1–11. https://doi.org/10.1145/2980179.2980255
9. Liu, J., Dong, J., Cai, X., Qi, L., & Chantler, M. (2015). Visual perception of procedural textures: Identifying perceptual dimensions and predicting generation models. PLOS ONE, 10(6). https://doi.org/10.1371/journal.pone.0130335
10. Peitgen, H. (2004). -O., Jürgens H., Saupe D. Chaos and Fractals: New Frontiers of Science / H.-O. Peitgen, H. Jürgens, D. Saupe. 10.1007/b97624. https://doi.org/10.1007/b97624
11. Perlin, K. (1985). An image synthesizer. Proceedings of the 12th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH ‘85), 287–296. https://doi.org/10.1145/325334.325247
12. Wei, B. (2006). -G., Li J.-P., Pang X.-B. Using texture synthesis in fractal pattern design. Journal of Zhejiang University-SCIENCE A, 7, 289–295. https://doi.org/10.1631/jzus.2006.A0289
13. Wei, L. (2000). -Y., Levoy M. Fast texture synthesis using tree-structured vector quantization. Proceedings of SIGGRAPH, 479–488. https://doi.org/10.1145/344779.345009
14. Worley, S. (1996). A cellular texture basis function. Proceedings of SIGGRAPH ‘96, 291–294. https://doi.org/10.1145/237170.237267
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 ECONOSCITECH INTEGRATION

This work is licensed under a Creative Commons Attribution 4.0 International License.
