Study and Comparison of Face Recognition based on PCA and 2DPCA

Abstract

Face recognition is an integral part of biometrics and has been an active research field of application. The face is a major focus of attention in social life playing an important role in conveying a person’s identity and emotions. A face recognition system is an application of computer which is capable of identifying or verifying a person from an image. Dimensionality reduction method plays a significant role for recognition of faces. Principal Component Analysis (PCA) and Two-Dimensional Principal Component Analysis (2DPCA) are commonly used technique for this approach. This paper performs a comparison between PCA and 2DPCA by implementing them on four standard databases. The test result gives maximum recognition rate of 93.5% for PCA and 96% for 2DPCA showing that 2DPCA is more efficient than PCA.

Authors and Affiliations

Chanchal Jain, Raj Kumar Sahu

Keywords

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  • EP ID EP22253
  • DOI -
  • Views 226
  • Downloads 4

How To Cite

Chanchal Jain, Raj Kumar Sahu (2016). Study and Comparison of Face Recognition based on PCA and 2DPCA. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 4(6), -. https://europub.co.uk./articles/-A-22253