Paper Info
Title
Bio-inspired Hybrid Face Recognition System for Small Sample Size and Large Dataset
Abstract
Face recognition has a great demands in human authentication and it becomes one of the most intensive field of biometrics research areas. In this paper, we present a bio-inspired face recognition system based on linear discriminant analysis and external clue i.e. geometrical features. The use of external clue helps to identify the face among very close match and secondly it also helps in the creation of small data set. The proposed approach is insensitive to large dataset and small sample size (SSS) and it provides 94.5% accuracy on BANCA face database. Experimental and simulation results shows that the proposed scheme has encouraging results for a practical face recognition system. The computational complexity of proposed system is more than conventional LDA due to the computation of weights during recognition and in external clue but on the other it provides significant performance gain especially on similar face database.
Year
DOI
Venue
2010
10.1109/IIHMSP.2010.99
IIH-MSP
Keywords
Field
DocType
small data,practical face recognition system,banca face database,face recognition,bio-inspired hybrid face recognition,bio-inspired face recognition system,external clue,large dataset,proposed system,proposed scheme,small sample size,similar face database,databases,face,principal component analysis,linear discriminant analysis,computational complexity,feature extraction,biometrics,accuracy
Computer vision,Facial recognition system,Small data,Authentication,Three-dimensional face recognition,Pattern recognition,Computer science,Feature extraction,Artificial intelligence,Biometrics,Linear discriminant analysis,Computational complexity theory
Conference
Citations 
PageRank 
References 
2
0.37
10
Authors
3
Name
Order
Citations
PageRank
Muhammad Imran Razzak122133.86
Muhammad Khurram Khan23538204.81
Khaled Alghathbar349832.54