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一种具有统计不相关性的最佳鉴别矢量集 被引量:51

AN OPTIMAL SET OF UNCORRELATED DISCRIMINANT FEATURES
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摘要 在模式识别领域,基于Fisher鉴别准则函数的Foley-Sam m on 最佳鉴别矢量集技术有着重大的影响.特征抽取的一般原则是最好抽取模式的不相关的特征,而Foley-Sam m on 最佳鉴别矢量集的诸鉴别特征是统计相关的.文中提出了一种具有统计不相关性的最佳鉴别矢量集,并给出了计算公式.对ORL人脸图像数据库作了实验,实验结果表明,具有统计不相关性的最佳鉴别矢量集有较强的特征抽取能力,优于Foley-Sam m on Based on Fisher's discriminant function, Foley Sammon's optimal set of discriminant vectors has great influence in the area of pattern recognition. A general rule for feature extraction is to extract features as uncorrelated as possible, but the discriminant vectors in Foley Sammon's optimal set are correlated. In the paper here, an optimal set of uncorrelated discriminant features is presented, and some formula to compute it is given. Experiments with ORL face image database have been performed. Experimental results show that new optimal set of uncorrelated discriminant features has powerful ability of feature extraction, and is superior to Foley Sammon's optimal set of discriminant vectors.
出处 《计算机学报》 EI CSCD 北大核心 1999年第10期1105-1108,共4页 Chinese Journal of Computers
基金 国家自然科学基金
关键词 模式识别 特征抽取 鉴别分析 人脸图像 图像识别 Pattern recognition, feature extraction, discriminant analysis, face recognition.
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