Infrared face recognition based on blood perfusion and fisher linear discrimination analysis

To get the good performance of infrared face recognition from the biological feature and statistical character, a novel method for infrared face recognition based on blood perfusion and fisher linear optimal discrimination is proposed in this paper. Firstly, thermal images are converted into blood perfusion domain by blood perfusion model to enlarge between-class distance and lessen within-class distance, which makes full use of the biological feature of the human face. Then, the FLD is chosen to maximize the ratio of between-class distance to within-class distance from the statistical scope. The experiments illustrate that transformation from thermal images to blood perfusion domain can enlarge the ratio of between-class distance to within-class distance and the method proposed in this paper has better performance compared with traditional methods.