IJAT Vol.10 No.2 pp. 209-213
doi: 10.20965/ijat.2016.p0209


A Digital Grain Generation Method Suitable for Geometric Textures

Ryoji Miyachi, Shin Usuki, and Kenjiro T. Miura

Shizuoka University
3-5-1 Jouhoku, Naka-ku, Hamamatsu, Shizuoka 432-8561, Japan

Corresponding author,

October 29, 2015
January 21, 2016
Online released:
March 4, 2016
March 5, 2016
texturing, graining, angle based flattening
The automated production of products using digital data has been realized in recent years through the development of manufacturing machines. Digital data are also used for automatic texturing. In a product texturing system using digital data, texture information needs to be incorporated in the generation of digital data. However, it is difficult to generate such data manually since it is not easy to fit the texture to the product or to prevent the texture pattern from being stretched or shortened. Therefore, what is needed is a method of automatically generating digital data that yields a seamless texture with little distortion and a method of fitting the texture to the product shape. In this paper, the application of the Angle Based Flattening (ABF) method by Sheffer and de Sturler to the generation of digital data of textures is proposed. Another method to extend the ABF technic to make it more suitable to geometric textures is also proposed.
Cite this article as:
R. Miyachi, S. Usuki, and K. Miura, “A Digital Grain Generation Method Suitable for Geometric Textures,” Int. J. Automation Technol., Vol.10 No.2, pp. 209-213, 2016.
Data files:
  1. [1] Y. Zhou, S. Zhang, S. Zhao, and H. Chen, “Computer Texture Mapping for Laser Texturing of Injection Mold,” Advances in Mechanical Engineering, Article ID 681563, 5pp., 2014.
  2. [2] H. Aoyama and S. Nakatsuka, “Study on Digital Style Design – Development of Wrinkle Pattern (Texture) Design System –,” The Journal of The Japan Society for Precision Engineering, Vol.75, No.7, pp. 847-852, 2009.
  3. [3] Y. Kobayashi, K. Shirai, Y. Hara, T. Mizoguchi, and K. Kawasaki, “Generation and Assessment of Random Surface Texture over a Wide Area,” IJAT, Vol.5, No.2, pp. 185-189, 2010.
  4. [4] D. Uzuyama, M. Kikuta, and K. T. Miura, “Development of a Grain Milling System by Use of Digital Data,” Computer-Aided Design & Applications, Vol.7, No.3, pp. 291-296, 2010.
  5. [5] K. T. Miura, D. Uzuyama, and M. Kikuta, “Extension of Image Quilting into 3D and Its Application to Grain Generation,” Computer-Aided Design & Applications, Vol.8, No.4, pp. 545-555, 2011, DOI: 10.3722/cadaps.2011.545-555.
  6. [6] D. Uzuyama, M. Kikuta, and K. T. Miura, “A Grain Generation Method for Large Die Data by Use of the Out-of-Core Method,” The Journal of The Japan Society for Precision Engineering, 2011.
  7. [7] C. N. Tang, D. Uzuyama, K. T. Miura, S. Usuki, and M. Kikuta, “A Grain Generation Method for Large Die Data Using the Out-of-Core Method,” Computer-Aided Design & Applications, Vol.9, No.6, pp. 915-923, 2012, DOI: 10.3722/cadaps.2012.915-923.
  8. [8] A. Sheffer and E. de Sturler, “Parameterization of faceted surfaces for meshing using angle based flattening,” Engineering with Computers, Vol.17, No.3, pp. 326-337, 2001.
  9. [9] A. Sheffer, B. L’evy, M. Mogilnitsky, and A. Bogomyakov, “ABF++: Fast and Robust Angle Based Flattening,” ACM Transactions on Graphics, Association for Computing Machinery, Vol.24, No.2, pp. 311-330, 2004.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Jul. 23, 2024