Face Recognition by Linear Discriminant Analysis

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Provided by: Interscience Open Access Journals
Topic: Security
Format: PDF
Linear Discriminant Analysis (LDA) has been successfully applied to face recognition which is based on a linear projection from the image space to a low dimensional space by maximizing the between class scatter and minimizing the within-class scatter. LDA allows objective evaluation of the significance of visual information in different features of the face for identifying the human face. The LDA also provides the users' with a small set of features that carry the most relevant information for classification purposes. LDA method overcomes the limitation of Principle Component Analysis (PCA) method by applying the linear discriminant criterion.
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