Title: An effective colour feature extraction method using evolutionary computation for face recognition
Authors: Peichung Shih, Chengjun Liu
Addresses: Healthcare Analytics and Database Marketing, CSG Marketing, Siemens Medical Solutions USA, Inc., Malvern, PA 19355, USA. ' Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102, USA
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.
Keywords: BEE; biometric experimentation environment; colour space; GAs; genetic algorithms; FRGC; face recognition; gallery; probe; query; target; biometrics; colour feature extraction; image representation.
International Journal of Biometrics, 2011 Vol.3 No.3, pp.206 - 227
Published online: 26 Jun 2011 *Full-text access for editors Access for subscribers Purchase this article Comment on this article