Ensemble classification based on correlation analysis for face recognition

This paper presents a new face recognition approach by using correlation analysis and ensemble classifiers based on support vector machine (SVM). In this approach, image pre-processing techniques such as histogram equalization, edge detection and geometrical transformation are first used in order to improve the quality of the face images. We further employ correlation analysis method to extract features. At last, ensemble classifiers based on SVM are selected to construct the classification committee using binary particle swarm optimization (BPSO). Comparisons with other popular classification methods show that our scheme is very promising in face recognition.