Comparison of Different Algorithm for Face Recognition
Keywords:
euclidean distance, false acceptance rate, false rejection rate, linear discriminant analysis, principle component analysis, scatter matrix
Abstract
This paper is about the different algorithms which are used for face recognition. There are so many algorithms which are available for face recognition .There are two approaches by which the face can be recognize i.e. face Geometry based and face appearance based. The appearance based technique is also sub divided into two technique i.e. local feature and global feature based. The technique of local feature based are Discrete Cosine Transform (DCT).In this paper we study the two global features (holistic) appearance based algorithm i.e. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) in which every face image is converted into 1D, we are using 1D for all the calculation and then compare these two algorithm with the help of FAR (False Acceptance Rate),FRR (False Rejection Rate),Time, Memory and checks which algorithm gives the better result.
Downloads
- Article PDF
- TEI XML Kaleidoscope (download in zip)* (Beta by AI)
- Lens* NISO JATS XML (Beta by AI)
- HTML Kaleidoscope* (Beta by AI)
- DBK XML Kaleidoscope (download in zip)* (Beta by AI)
- LaTeX pdf Kaleidoscope* (Beta by AI)
- EPUB Kaleidoscope* (Beta by AI)
- MD Kaleidoscope* (Beta by AI)
- FO Kaleidoscope* (Beta by AI)
- BIB Kaleidoscope* (Beta by AI)
- LaTeX Kaleidoscope* (Beta by AI)
How to Cite
Published
2013-10-15
Issue
Section
License
Copyright (c) 2013 Authors and Global Journals Private Limited
This work is licensed under a Creative Commons Attribution 4.0 International License.