Current Proceedings on Technology
Face database compression by hotelling transform using a new method
Yazarlar: Mostafa Mofarreh-Bonab, Mohamad Mofarreh-Bonab
Cilt 1 , Sayı - , 2012 , Sayfalar -
Konular:-
Anahtar Kelimeler:Hotelling,Compression ratio,Eigen Face,Eigen value,Eigen vector,Principal Component Analysis,
Özet: Principal Component Analysis (PCA) is a method for compressing high dimensional databases [1]. If it used for image compression, it called Hotelling or KL transform. This method extracts q Eigen vectors and q Eigen values for database [2]. The quality of retrieved images various and some of them have very low quality. In this paper an optimized PCA method is introduced which can increase the quality of reconstructed images focusing on very noisy images.
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BibTex
KOPYALA
@article{2012, title={Face database compression by hotelling transform using a new method}, volume={1}, number={0}, publisher={Current Proceedings on Technology }, author={Mostafa Mofarreh-Bonab, Mohamad Mofarreh-Bonab}, year={2012} }
APA
KOPYALA
Mostafa Mofarreh-Bonab, Mohamad Mofarreh-Bonab. (2012). Face database compression by hotelling transform using a new method (Vol. 1). Vol. 1. Current Proceedings on Technology .
MLA
KOPYALA
Mostafa Mofarreh-Bonab, Mohamad Mofarreh-Bonab. Face Database Compression by Hotelling Transform Using a New Method. no. 0, Current Proceedings on Technology , 2012.