Feature extraction is an important and critical step in the process of face recognition

a feature extraction algorithm based on uncorrelated discriminant locality preserving is proposed

and its application in face recognition is carried out. Laplacianface which is based on locality preserving projection is an effective algorithm

but it only takes the locality into account

thus the extracted features might be highly correlated

and it does not consider the class information. Some improved algorithms consider the discrimiant information

but the interclass information is not considered. The algorithm proposed here not only imposes an uncorrelated constraint to reduce data redundancy

but also utilizes the class information and the interclass separability after projection is enhanced. Experiments validate the correctness and effectiveness of the algorithm

and prove that the proposed algorithm has better performance.