A Survey Paper on Different Algorithms used for Fake Biometric Detection |
Author(s): |
| Madhavi Babasaheb Danane , Annasaheb Dange College of Engineering and Technology, Ashta.; Vikram A. Mane, Annasaheb Dange College of Engineering and Technology, Ashta. |
Keywords: |
| Face Recognition Techniques, Biometrics, Linear Binary Pattern (LBP), Support Vector Machine (SVM), Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Difference of Guassian Method (DoG), Grey Level Co-Occurrence Matrix Methods (GLCM), Quadratic Discriminant Analysis (QDA) |
Abstract |
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The objective of this study is to compare different algorithms which make use of image quality measures for fake biometric detection. Recently, many applications are based on face recognition techniques including video surveillance, law enforcement, and identity authentication. These systems are widely used online and provide a very fast recognition rate. Face recognition is very important especially in uncontrolled environment. It is a challenging task to recognize faces due to illumination, occlusion, pose variation, expressions, aging factors and alignment etc. There are different methods used to identify whether the object is fraudulent or genuine. This paper gives idea about previous researches and their findings. |
Other Details |
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Paper ID: IJSRDV4I50786 Published in: Volume : 4, Issue : 5 Publication Date: 01/08/2016 Page(s): 1459-1462 |
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