Facial Identification System Using Eigenfaces |
Author(s): |
| Snehal Dhole , Sipna College of Engineering and Technology,Amravati; Dr. P. A. Tijare, Sipna College of Engineering and Technology |
Keywords: |
| Face recognition, JAFFE, PCA, Eigenface, Euclidian, Yale |
Abstract |
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Principal component analysis (PCA) method called Eigenface is used to identify faces. The Eigenface technique finds the optimal vector for dispersing the facial image in the facial space while lowering the number of dimensions. This technique has been widely used and put to use in earlier studies to identify images of human faces. PCA can recognize photographs with various expressions in addition to detecting human faces in usual circumstances. Even images of faces that have been altered in some way can be recognized using techniques like combining photos of faces after plastic surgery with facial image restoration. This study's goal is to assess how well the PCAEigenface technique performs when recognizing human faces in pictures from various datasets. each with a unique set of challenges. Each database's well-known accuracy spans from 99% to 67%, with an average identification rate of around 85%. |
Other Details |
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Paper ID: IJSRDV11I50065 Published in: Volume : 11, Issue : 5 Publication Date: 01/08/2023 Page(s): 124-127 |
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