Paper Info
Title
Embedded face recognition based on fast genetic algorithm for intelligent digital photography
Abstract
In this paper, we propose embedded face recognition (FR) to use in intelligent image system. For efficient FR VLSI design, we use a feature selection and feature extraction method based on Gabor wavelets using a fast genetic algorithm (FGA). Many FR systems are based on Gabor wavelet due to its desirable characteristics of spatial locality and orientation selectivity. However, the process of searching for features with Gabor wavelet is computationally expensive and has an unusual sensibility for variations such as illumination. To overcome these problems and use in real-time applications, we optimize Gabor wavelet's parameters of translation, orientations and scales, which make it approximates a local image contour region by the use of hardware oriented FGA. From experimental results, we certify that our method shows recognition rate of over 97.27 % for FERET dataset, which exceeds the performance of the other popular methods
Year
DOI
Venue
2006
10.1109/TCE.2006.1706463
IEEE Trans. Consumer Electronics
Keywords
Field
DocType
Face recognition,Genetic algorithms,Digital photography,Feature extraction,Facial features,Data mining,Intelligent systems,Lighting,Image storage,Very large scale integration
Computer vision,Facial recognition system,Locality,Feature selection,Pattern recognition,Gabor wavelet,Computer science,Feature extraction,Artificial intelligence,Very-large-scale integration,Genetic algorithm,Wavelet transform
Journal
Volume
Issue
ISSN
52
3
0098-3063
Citations 
PageRank 
References 
15
0.78
16
Authors
5
Name
Order
Citations
PageRank
Dong-Sun Kim162850.14
In-Ja Jeon2303.57
Seung-yerl Lee3296.44
Phill-Kyu Rhee4333.58
Duck-jin Chung56211.44