Impact of Kernel Fisher Analysis Method on Face Recognition

Provided by: International Journal of Engineering and Advanced Technology (IJEAT)
Topic: Security
Format: PDF
Human face recognition is a challenging task in computer vision and pattern recognition. Face recognition is difficult because it is a real world problem. The human face is complex, natural object that tends not to have easily identified edges and features. Because of this, it is difficult to develop a mathematical model of that face that can be used as prior knowledge when analyzing a particular image. This paper deals with the correspondence presents color and frequency features based face recognition. The CFF method, which applies an Enhanced Fisher Model (EFM), extracts the complementary frequency features in a new hybrid color space for improving face recognition performance.

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