Soft Computing

, Volume 22, Issue 2, pp 477–486 | Cite as

An improved genetic algorithm for three-dimensional reconstruction from a single uniform texture image

  • Yujuan Sun
  • Xiaofeng Zhang
  • Muwei Jian
  • Shengke Wang
  • Zeju Wu
  • Qingtang Su
  • Beijing Chen
Methodologies and Application

Abstract

Three-dimensional reconstruction from a single input image is a very difficult issue, especially for the texture images. Moreover, the unknown lighting parameters also make this problem more complex. In this paper, an improved genetic algorithm has been proposed to reconstruct the 3D shape from a single texture image with similar appearances. The proposed scheme contains three main steps: first, the lighting parameters has been estimated by detecting and analyzing the intensity information of the input texture image; then, the initial surface normal, which can be used as the initial population of generic algorithm, has been calculated by combining the patch matching and stitching method; finally, the improved genetic algorithm incorporating spatial information is implemented, which can search the minimum starting from the surface normals of the neighborhood. Experiment results verified the effectiveness of the proposed method according to realistic visual-perception.

Keywords

Texture image 3D reconstruction Photometric stereo Genetic algorithm 

Notes

Acknowledgments

This work was supported by National Natural Science Foundation Of China (61602229, 61301241, 61501278, and 61601427); Natural Science Foundation of Shandong (ZR2015FQ011; ZR2015FQ013); China Postdoctoral Science Foundation funded Project (2016M590659); Qingdao Postdoctoral Science Foundation funded Project (861605040008); The Priority Academic Program Development of Jiangsu Higer Education Institutions, Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology (CICAEET).

Compliance with ethical standards

Conflicts of interest

Yujuan Sun, Xiaofeng Zhang, Muwei Jian, Shengke Wang, Zeju Wu, Qingtang Su and Beijing Chen declare that they have no conflict of interest.

Human and Animals rights

This article does not contain any studies with human participants or animals performed by any of the authors.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Yujuan Sun
    • 1
  • Xiaofeng Zhang
    • 1
  • Muwei Jian
    • 2
  • Shengke Wang
    • 2
  • Zeju Wu
    • 3
  • Qingtang Su
    • 1
    • 4
  • Beijing Chen
    • 4
  1. 1.School of Information and Electrical EngineeringLudong UniversityYantaiChina
  2. 2.Department of Computer Science and TechnologyOcean University of ChinaQingdaoChina
  3. 3.School of Communication and Electronic EngineeringQingdao University of TechnologyQingdaoChina
  4. 4.School of Computer and SoftwareNanjing University of Information Science and TechnologyNanjingChina

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