Abstract
This paper presents a colour feature extraction method using a Genetic Algorithm (GA) to seek the optimal colour space transformation that leads to an effective image representation for face recognition. A new colour space, LC1C2, consisting of one luminance (L) channel and two chrominance channels (C1, C2) is introduced as a linear transformation of the input RGB colour space. The specific transformation from the RGB colour space to the LC1C2 colour space is optimised by a GA where a fitness function guides the evolution towards higher recognition accuracy.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 206-227 |
| Number of pages | 22 |
| Journal | International Journal of Biometrics |
| Volume | 3 |
| Issue number | 3 |
| DOIs | |
| State | Published - Jun 2011 |
| Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Computer Vision and Pattern Recognition
- Computer Science Applications
- Electrical and Electronic Engineering
- Applied Mathematics
Keywords
- BEE
- Biometric experimentation environment
- Colour space
- FRGC
- Face recognition grand challenge
- GAs
- Gallery
- Genetic algorithms
- Probe
- Query
- Target