GDL

New Modelling of Modified Two Dimensional Fisherface Based Feature Extraction

Journal from gdlhub / 2016-11-12 02:55:04
Oleh : Arif Muntasa, Telkomnika
Dibuat : 2014-03-01, dengan 1 file

Keyword : Biometric, Face Recognition, Principal Component Analysis, Two Dimensional Linear Discriminant Analysis.
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/20

Biometric researches have been interesting field for many researches included facial recognition. Crucial process of facial recognition is feature extraction. One Dimensional Linear Discriminant Analysis is one of feature extraction method is development of Principal Component Analysis mostly used by researches. But, it has limitation, it can efficiently work when number of training sets greater or equal than number of dimensions of image training set. This limitation has been overcome by using Two Dimensional Linear Discriminant Analysis. However, search value of matrix identity R and L by using Two Dimensional Linear Discriminant Analysis takes high cost, which is O(n3). In this research, the seeking of “Scatter between Class” and “Scatter within Class” by using Discriminant Analysis without having to find the value of R and L advance are proposed. Time complexity of proposed method is O(n2). Proposed method has been tested by using AT&T face image database. The experimental results show that maximum recognition rate of proposed method is 100%.

Deskripsi Alternatif :

Biometric researches have been interesting field for many researches included facial recognition. Crucial process of facial recognition is feature extraction. One Dimensional Linear Discriminant Analysis is one of feature extraction method is development of Principal Component Analysis mostly used by researches. But, it has limitation, it can efficiently work when number of training sets greater or equal than number of dimensions of image training set. This limitation has been overcome by using Two Dimensional Linear Discriminant Analysis. However, search value of matrix identity R and L by using Two Dimensional Linear Discriminant Analysis takes high cost, which is O(n3). In this research, the seeking of “Scatter between Class” and “Scatter within Class” by using Discriminant Analysis without having to find the value of R and L advance are proposed. Time complexity of proposed method is O(n2). Proposed method has been tested by using AT&T face image database. The experimental results show that maximum recognition rate of proposed method is 100%.

Beri Komentar ?#(0) | Bookmark

Properti	Nilai Properti
ID Publisher	gdlhub
Organisasi	Telkomnika
Nama Kontak	Herti Yani, S.Kom
Alamat	Jln. Jenderal Sudirman
Kota	Jambi
Daerah	Jambi
Negara	Indonesia
Telepon	0741-35095
Fax	0741-35093
E-mail Administrator	elibrarystikom@gmail.com
E-mail CKO	elibrarystikom@gmail.com