Innertron: New Methodology of Facial Recognition, Part I

  • Rory A. Lewis
  • Zbigniew W. Raś
Conference paper
Part of the Advances in Soft Computing book series (AINSC, volume 31)


On October 10, 2001, the US President identified the most wanted persons sought by the United States of America. Agencies such as FBI, CIA and Homeland Security spread images of the most wanted persons across the United States. Even though US citizens saw their images on television, the Internet and posters, computers had, and still have for that matter, no ability at all to identify these persons. To date FBI, CIA and Homeland Security depend entirely on human beings, not computers, to identify persons at borders and international airports. In other words, facial recognition remains an incompetent technology.

Accordingly, authors first succinctly show the weaknesses of the current facial recognition methodologies, namely Eigenface Technology, Local Feature Analysis (from the classical 7 point to the 32–50 blocks approach), the Scale-Space Approach, Morphological Operations and industrial or patented methodologies such as ILEFIS™, Viisage™, Visionics™ and Cognitec’s FaceVACS-Logon™, Identix™ and Neven Vision™. Secondly, they introduce a completely new, simple and robust methodology called Innertron.


Facial Recognition Homeland Security Lateral Rectus Facial Hair Lateral Commissure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Rory A. Lewis
    • 1
  • Zbigniew W. Raś
    • 1
    • 2
  1. 1.Computer Science Dept.UNC-CharlotteCharlotteUSA
  2. 2.Institute of Computer SciencePolish Academy of SciencesWarsawPoland

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