Algorithms 2DPCA for face recognition

  • N. Shchegoleva
  • Georgy Kukharev
Keywords: a two-dimensional Karhunen-Loeve transformation, the use in the business applications, Two-dimensional principal component analysis, the face recognition

Abstract

In article presents algorithms for two-dimensional principal component analysis (Two-dimensional Principal Component Analysis - 2D PCA)-oriented processing of digital images of large sizes in a small sample. Algorithms based on direct calculation of two covariance matrices for all source images without converting them into vectors. Evaluated characteristics of the presented algorithms. We discuss possibilities presented by the use of algorithms in other areas.

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Published
2011-02-05
How to Cite
ShchegolevaN., & KukharevG. (2011). Algorithms 2DPCA for face recognition. BUSINESS INFORMATICS, 5(4), 31-38. Retrieved from https://vo.hse.ru/index.php/bijournal/article/view/26273
Section
Software engineering