摘要
对广义最佳鉴别矢量的求解方法进行研究,根据矩阵的扰动理论和广义K-L变换,提出了一种改进的求解广义最佳鉴别矢量集的解析算法。由于该算法一次性地求出了所有广义最佳鉴别矢量,而无需迭代,因而节约了计算时间,且识别率高。在ORL人脸数据库的数值实验,验证了上述论断的正确性。
A study was made on the solving method of the generalized optimal set of discriminant vectors. An improved analytical algorithm of the generalized optimal set of discriminant vectors was proposed based on the combination of perturbation theory and the K-L transformation. The computational time was saved because all the discriminant vectors were obtained simultaneously with the proposed algorithm, while it did not need iteration. Furthermore, the new algorithm yielded high recognition rate. These statements are supported by the numerical simulation experiments conducted on ORL face database.
出处
《系统仿真学报》
CAS
CSCD
北大核心
2006年第z2期906-908,共3页
Journal of System Simulation
基金
国家自然科学基金(60472060
60572034)
图像处理与通信实验室开放基金(KJS03038)
江苏省自然科学基金(BK2004058
BK2006081)
中国科学院沈阳自动化研究所机器人学重点实验室基金(RL200108)。
关键词
模式识别
特征抽取
鉴别分析
广义最佳鉴别矢量集
人脸识别
pattern recognition
feature extraction
disciminant analysis
generalized optimal set of discriminant vectors
face recognition