Journal of Information Processing Systems

Korea Information Processing Society (한국정보처리학회)
권호 표지
DOI QR코드

DOI QR Code

Research on Pattern Elements and Colors in Apparel Design through Fractal Theory

  • Dan Li (School of Arts and Design, Harbin University) ;
  • Chengjun Yuan (School of Information Engineering, Harbin University)
  • Received : 2023.06.14
  • Accepted : 2023.08.26
  • Published : 2024.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

Excellent apparel design can increase market competitiveness. This article briefly introduced the theory of fractals and its application in the field of apparel design. The convolutional neural network (CNN) algorithm was used to assist in the evaluation of apparel designs. In the case analysis, the accuracy of the evaluation was validated by comparing the CNN algorithm with two other intelligent algorithms, support vector machine (SVM) and back propagation (BP). The evaluation of the proposed design showed that compared with SVM and BP algorithms, the CNN algorithm had higher accuracy in evaluating apparel designs. The evaluation result of the proposed apparel design not only further verifies the effectiveness of the CNN algorithm, but also demonstrates that the theory of fractals can be effectively applied in apparel design to provide more innovative designs.

Keywords

References

  1. S. H. So and M. J. Chang, "Korean costumes design II by analysis of characters of classical novel 'Guunmong'," Journal of Korean Traditional Costume, vol. 19, no. 4, pp. 125-136, 2016. https://doi.org/10.16885/jktc.2016.12.19.4.125 
  2. K. M. Lee, "A study on the construction of court dress Coat in the Daehan Empire," Journal of the Korean Society of Costume, vol. 66, no. 6, pp. 17-31, 2016. https://doi.org/10.7233/jksc.2016.66.6.017 
  3. B. Brownie, "Zero-gravity wardrobes: The behaviour of costume in weightless environments," Film, Fashion & Consumption, vol. 9, no. 1, pp. 5-21, 2020. https://doi.org/10.1386/ffc_00009_1 
  4. S. H. Kim and K. S. Chae, "The fractal phenomenon appeared in the formativeness of Korean traditional costume," Journal of the Korea Fashion & Costume Design Association, vol. 18, no. 3, pp. 165-181, 2016. 
  5. L. Zhang, Z. Xu, and Y. Zhang, "Realization of clothing image contour extraction and collar segmentation," Journal of Physics: Conference Series, vol. 1790, no. 1, article no. 012091, 2021. https://doi.org/10.1088/1742-6596/1790/1/012091 
  6. M. Artemenko, O. Yakymchuk, D. Yakymchuk, N. Myrhorodska, and I. Zasornova, "Costume designin for hospitality establishments staff on the basis of analysis the Slavic snakes ornamentation," Vlakna a Textil, vol. 25, no. 1, pp. 3-7, 2018. 
  7. J. Zou, P. Yu, W. Wang, X. Tong, C. Le, C. Wu, et al., "Broadband mid-infrared perfect absorber using fractal Gosper curve," Journal of Physics D: Applied Physics, vol. 53, no. 10, article no. 105106, 2019. https://doi.org/10.1088/1361-6463/ab57ea 
  8. H. Guo, B. Ying, X. Zhang, and J. Qi, "Acquisition of plate-making process knowledge for smart clothing CAD systems," Journal of Fiber Bioengineering and Informatics, vol. 12, no. 3, pp. 137-145, 2019. https://doi.org/10.3993/jfbim00295 
  9. J. Qian and M. Zhao, "Research status and development of clothing mass customization," Journal of Physics: Conference Series, vol. 1790, no. 1, article no. 012045, 2021. https://doi.org/10.1088/1742-6596/1790/1/012045 
  10. B. K. Kim, G. Kim, and S. Y. Lee, "Style-controlled synthesis of clothing segments for fashion image manipulation," IEEE Transactions on Multimedia, vol. 22, no. 2, pp. 298-310, 2020. https://doi.org/10.1109/TMM.2019.2929000 
  11. I. Chtioui, F. Bossuyt, M. de Kok, J. Vanfleteren, and M. H. Bedoui, "Arbitrarily shaped rigid and smart objects using stretchable interconnections," IEEE Transactions on Components Packaging & Manufacturing Technology, vol. 6, no. 4, pp. 533-544, 2016. https://doi.org/10.1109/TCPMT.2015.2511077 
  12. S. Wang, Y. Huang, and J. A. Rogers, "Mechanical designs for inorganic stretchable circuits in soft electronics," IEEE Transactions on Components Packaging & Manufacturing Technology, vol. 5, no. 9, pp. 1201-1218, 2015. https://doi.org/10.1109/TCPMT.2015.2417801 
  13. A. K. Bhandari, A. Kumar, S. Chaudhary, and G. K. Singh, "A novel color image multilevel thresholding based segmentation using nature inspired optimization algorithms," Expert Systems with Applications, vol. 63, pp. 112-133, 2016. https://doi.org/10.1016/j.eswa.2016.06.044 
  14. D. Lee and K. N. Plataniotis, "Toward a no-reference image quality assessment using statistics of perceptual color descriptors," IEEE Transactions on Image Processing, vol. 25, no. 8, pp. 3875-3889, 2016. https://doi.org/10.1109/TIP.2016.2579308 
  15. C. Li, J. Guo, and C. Guo, "Emerging from water: underwater image color correction based on weakly supervised color transfer," IEEE Signal Processing Letters, vol. 25, no. 3, pp. 323-327, 2018. https://doi.org/10.1109/LSP.2018.2792050