DOIONLINE 
DOIONLINE Publish In |
International Journal of Advances in Electronics and Computer Science-IJAECS |
 Journal Home Volume Issue |
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Issue |
Volume-9,Issue-11 ( Nov, 2022 ) | |||||||||
Paper Title |
A Review Paper on Face Recognition Methods | |||||||||
Author Name |
Ragini, Poorti Bajaj, Neha Singh | |||||||||
Affilition |
1Student, Indira Gandhi Delhi Technical University for Women, Madrasa Road opposite to St. James Church, Kashmere Gate, Delhi 110006, India 2Student, Indira Gandhi Delhi Technical University for Women, Madrasa Road opposite to St. James Church, Kashmere Gate, Delhi 110006, India 3Asssistant Professor, Indira Gandhi Delhi Technical University for Women, Madrasa Road opposite to St. James Church, Kashmere Gate, Delhi 110006, India | |||||||||
Pages |
1-5 | |||||||||
Abstract |
Abstract - Face Recognition is a way of detecting and identifying an individual's identity by making use of biometric methods and avoiding any physical contact with the machine. Beyond security and law enforcement, the applications of this technology is widely spread. From making our phones less prone to the theft of sensitive and personal information using FaceIDs to accessing patients' records, and keeping a check on their registrations and emotions through the face recognition system in the healthcare industry, we are making progress in every field that this technology can provide. From using the Snapchat and Instagram filters to using Google Photos to sort and tag the images of people in the pool of your memories. These all have been made possible by the use of Face Recognition and identification technology. In this paper, we have made an attempt to review some of the methods which are being extensively used in the era of face recognition. This includes Principal Component Analysis (PCA), Face Recognition, Convolutional Neural Networks (CNN), Viola-Jones, and Linear Discriminant Analysis (LDA). We have also made sure that this review includes the factors which affect the accuracy of recognition of face like orientation, alignment, pose, illumination, and expressions for better and more reliable results. Moreover, in the detection, identification, and processing phase, the main goal is to deliver accurate results in order to avoid false identification and enforce authentication using ID verification services. Keywords - Principal Component Analysis (PCA), Face Recognition, Support Vector Machine (SVM), Convolutional Neural Networks (CNN), Viola-Jones, Linear Discriminant Analysis (LDA). | |||||||||
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