A Linearization-Based Hybrid Approach for 3D Reconstruction of Objects in a Single Image

Kotan M., Öz C., Kahraman A.

International Journal of Applied Mathematics and Computer Science, vol.31, no.3, pp.501-513, 2021 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 31 Issue: 3
  • Publication Date: 2021
  • Doi Number: 10.34768/amcs-2021-0034
  • Journal Name: International Journal of Applied Mathematics and Computer Science
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, INSPEC, zbMATH, Directory of Open Access Journals
  • Page Numbers: pp.501-513
  • Keywords: 3D reconstruction, image comparison, shape from shading, shape recovery, surface inspection
  • Recep Tayyip Erdoğan University Affiliated: No


The shape-from-shading (SFS) technique uses the pattern of shading in images in order to obtain 3D view information. By virtue of their ease of implementation, linearization-based SFS algorithms are frequently used in the literature. In this study, Fourier coefficients of central differences obtained from gray-level images are employed, and two basic linearization-based algorithms are combined. By using the functionally generated surfaces and 3D reconstruction datasets, the hybrid algorithm is compared with linearization-based approaches. Five different evaluation metrics are applied on recovered depth maps and the corresponding gray-level images. The results on defective sample surfaces are also included to show the effect of the algorithm on surface reconstruction. The proposed method can prevent erroneous estimates on object boundaries and produce satisfactory 3D reconstruction results in a low number of iterations.