Soft Computing

, Volume 22, Issue 4, pp 1351–1360 | Cite as

Face image retrieval: super-resolution based on sketch-photo transformation

  • Shu Zhan
  • Jingjing Zhao
  • Yucheng Tang
  • Zhenzhu Xie
Methodologies and Application
  • 162 Downloads

Abstract

Considering the crucial role of face image in modern intelligent system, face image retrieval has attracted more attention for authentication, surveillance, law enforcement, and security control. In most cases, we cannot obtain the suspect’s face image directly and the best substitute is a face sketch of criminal suspect drawn by artist according to eyewitness description. It is a key step in the criminal investigation process to narrow down criminal suspect using the face sketch. At first, the face sketch is transformed to a pseudo-photo for subsequent utilization. Transformation is performed according to the classic eigenface algorithm and enhanced by super-resolution. Matching between reconstructed pseudo-photo and real face photographs is performed by Hash encoding and iterative quantization. We carried out our ideas on two public face databases, and the sketch face images are generated by photo-shopping software program. The experimental results show that the corresponding face images can be retrieved according to the input face sketch and super-resolution can effectively enhance the image quality and detail information of the pseudo-photo. Hash encoding and iterative quantization achieve the quick search of approximate face images.

Keywords

Face retrieval Super-resolution Iterative quantization Hash encoding Dictionary learning 

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grants 61371156, Anhui Province Science and Technology Research Programs under Grant 1401B042019. The authors would like to thank the anonymous reviewers for their helpful and constructive comments and suggestions.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Shu Zhan
    • 1
  • Jingjing Zhao
    • 1
  • Yucheng Tang
    • 1
  • Zhenzhu Xie
    • 1
  1. 1.Hefei University of TechnologyHefeiChina

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