المقتنيات: Face recognition using integrated discrete cosine transform and kernel fisher discriminant analysis

Face recognition using integrated discrete cosine transform and kernel fisher discriminant analysis

In face recognition applications, the dimension of the sample space is usually larger than the number of the samples in a training set. As a result, Fisher Linear Discriminant Analysis (FLD) based methods suffers due to singularity problem (of scatter matrix). This situation is often referred as &qu...

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التفاصيل البيبلوغرافية
المؤلفون الرئيسيون:	Janahiraman T.V., Omar J., Farukh H.N.
مؤلفون آخرون:	35198314400
التنسيق:	Conference paper
منشور في:	2023
الموضوعات:	Computer science Cosine transforms Discrete cosine transforms Discriminant analysis Feature extraction Fisher information matrix Learning algorithms Nonlinear analysis Complex data Face images Fisher linear discriminant analysis High-dimensional Input sample Kernel fisher discriminant analysis Linear algorithms Nonlinear features Nonlinear kernel functions ORL database Recognition accuracy Sample space Scatter matrix Singularity problems Small Sample Size Training sets Face recognition
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Face recognition using integrated discrete cosine transform and kernel fisher discriminant analysis

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