Face recognition using fusion of PCA and LDA: Borda count approach

Face recognition has become one of the most successful applications in the field of image analysis and understanding. This paper presents a new approach for identity recognition using rank-level fusion of multiple face representations. In this paper, we propose face recognition based on fusion of two well-known appearance-based techniques, Principal Component Analysis and Linear Discriminant Analysis. Fusion is done at rank level using Borda count method. Our experimental work demonstrates significant improvement in recognition accuracy over individual face representations.