特征提取是人脸识别过程中的一个重要步骤，是人脸识别算法有效性的关键。提出了一种基于无关性判别保局的特征提取算法，并应用于人脸识别。基于保局投影算法的人脸识别是一种有效的人脸识别算法，但它只考虑了数据的局部性，没有考虑类别信息，也没有考虑所提特征之间的相关性，现有的改进算法虽然考虑了类别信息，但是没有考虑到类间信息。本文算法使得所提特征之间相互无关，这样降低了数据冗余，同时考虑到类别信息，使得投影后的类间区分度加强了。实验结果验证了算法的正确性和有效性，比传统算法有较好的识别性能。

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.