Efficient Face Features Extraction and Recognition Using Principal Component Analysis

Authors

  • Dr. R. Pradeep Kumar Reddy
  • Dr. S. Kiran

DOI:

https://doi.org/10.46243/jst.2021.v6.i04.pp251-257

Keywords:

Face recognition, Machine learning, principsal component analysi

Abstract

: Face recognition is a common issue in artificial intelligence. This program was widely used in our daily lives. Several smart phones used facial recognition to open them. Face identification system is intended to protect personal information. When Face book people appear in photos, you may instantly recognize them. Face recognition has already been tackled in a number of ways. Until recently, it has been recommended, but it is still quite tough in the real world Circumstances. A key strategy for distinguishing persons is based on under a variety of conditions, such as partial facial blockage, lighting, and a wide range of postures. The goal of this paper is to create a face recognition system using a machine learning system. A method named principal component analysis (PCA) has been developed to recognize faces. Furthermore, it has been successful tested with 97 percent recognition accuracy by using PCA.

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Published

2021-08-29

How to Cite

Dr. R. Pradeep Kumar Reddy, & Dr. S. Kiran. (2021). Efficient Face Features Extraction and Recognition Using Principal Component Analysis. Journal of Science & Technology (JST), 6(4), 251–257. https://doi.org/10.46243/jst.2021.v6.i04.pp251-257