Learning the best subset of local features for face recognition
Pattern Recognition
Image denoising with neighbour dependency and customized wavelet and threshold
Pattern Recognition
Use of multiple contexts for real time face identification
MIRAGE'07 Proceedings of the 3rd international conference on Computer vision/computer graphics collaboration techniques
Face recognition via direct search optimized Gabor filters
ICOSSE'06 Proceedings of the 5th WSEAS international conference on System science and simulation in engineering
A fast method of lighting estimate using multi-linear algebra
SINOBIOMETRICS'04 Proceedings of the 5th Chinese conference on Advances in Biometric Person Authentication
Selection of wavelet subbands using genetic algorithm for face recognition
ICVGIP'06 Proceedings of the 5th Indian conference on Computer Vision, Graphics and Image Processing
| Hi-index | 0.00 |
Detecting and recognizing face images automatically is a difficu lt task due to the variability of illumination, presentation angle, face expression and other common problems of machine vision. In this paper, we represent face images as combinations of 2-D Gabor wavelet basis which are non-orthogonal. Genetic Algorithm (GA) is used to find an optimal basis derived from a combination of frequencies and orientation angles in the 2-D Gabor wavelet transform. Instead of using the widely used within and between class scatter evaluation as the fitness function in GA, we use entropy to measure the information complexity of the wavelet transform. Compared to the well-known "eigenface" algorithm which represents face images based on an orthogonal basis, this Gabor wavelet representation with optimal basis can provide a more accurate and effic ient projection scheme and therefore a better classification result.