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Fast face recognition based on fractal theory

Author

Listed:
  • Tang, Zhijie
  • Wu, Xiaocheng
  • Fu, Bin
  • Chen, Weiwei
  • Feng, Hao

Abstract

Nowadays, people are more and more concerned about accuracy, rapidity and convenience in the process of personal identification. In the field of biology and computer vision, a variety of methods have been proposed, while a proper method for face recognition is still a challenge. Although some reliable systems and advanced methods have been introduced under relatively controlled conditions, their recognition rate or speed is not satisfactory in the general settings. This is especially true when there are variations in pose, illumination, and facial expression. This paper proposed a fast face recognition method based on fractal theory. This method is to compress the facial images to obtain fractal codes and complete face recognition with these codes. Experimental results on Yale, FERET and CMU PIE databases demonstrate the high efficiency of our method in runtime and correct rate.

Suggested Citation

  • Tang, Zhijie & Wu, Xiaocheng & Fu, Bin & Chen, Weiwei & Feng, Hao, 2018. "Fast face recognition based on fractal theory," Applied Mathematics and Computation, Elsevier, vol. 321(C), pages 721-730.
    • Handle: RePEc:eee:apmaco:v:321:y:2018:i:c:p:721-730
    DOI: 10.1016/j.amc.2017.11.017
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    Cited by:

    1. Zining Wang & Jiawei Chen & Junlin Hu, 2022. "Multi-View Cosine Similarity Learning with Application to Face Verification," Mathematics, MDPI, vol. 10(11), pages 1-13, May.

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