关键词: 信息处理技术, 人脸识别, Fisher无相关鉴别矢量集, 核映射

Abstract: An algorithm for the uncorrelated discriminant vectors set based on the kernel mapping was proposed to solve the nonlinear classification problem of the face recognition. Applying the concept of the kernel function in the supporting vector machine, the nonlinear classification problem in the original space was transformed to the linear classification problem in the feature space by the kernel mapping, and the uncorrelated discriminant vectors set was solved in the feature space. The advantage of the algorithm consists in that the nonlinear problem can be transformed to the linear one, and the high order statistical features among the pixels of the face image can be extracted at the same time. The experiments in the ORL face database showed that the proposed algorithm is characterized by a higher recognition rate than the traditional algorithms for the global orthogonal and the uncorrelated discriminant vectors sets, and the highest recognition rate may reach 99%.

Key words: information processing, face recognition, Fisher uncorrelated set of discriminant vectors, kernel mapping