000			02916nam a2200313Ia 4500
001			77209
003			ft3963
005			20251106180942.0
008			190327n 000 0 eng d
040			_erda
041			_aengtag
050			_aQA76 L35 2005
082			_a.
100			_aDon Angelo Lalicon and Opalyne Jamoralin.
245		0	_aAn enhancement of LDA algorithm for face recognition
264			_a. _b. _cc2005
300			_bUndergraduate Thesis: (BSCS major in Computer Science) -Pamantasan ng Lungsod ng Maynila, 2005.
336			_b. _atext _2rdacontent
337			_30 _b. _aunmediated _2rdamedia
338			_30 _b. _avolume _2rdacarrier
347			_a0
385			_a2
505			_aABSTRACT: This research paper LDA (Linear Discriminant Algorithm) for Face Recognition was inspired by the previous thesis “Human Face Detection and Recognition” by Christine Joy Espiritu and Aaron James Singson. In face recognition, many techniques have been proposed. Among them, the most notable is a two-stage PCA+LDA approach Principal Component Analysis (PCA) is used to project images from the original image space into a face-subspace, where dimensionality is reduced and is no longer degenerate, so that LDA can proceed without trouble, PCA (Principal Component Analysis) and LDA (Linear Discriminant Analysis) are methods commonly used for face recognition and verification PCA was used in Human Face Dtection and Recognition by the previous proponents in developing their paper. However, there is a certain research “An Efficient LDA Algorithm for Face Recognition” by Jie yang, Hua Yu and William Kunz that proves that LDA algorithms outperformed the PCA. On the other hand, there are certain issues that haunt the LDA algorithm.
520			_aABSTRACT: This research paper LDA (Linear Discriminant Algorithm) for Face Recognition was inspired by the previous thesis Human Face Detection and Recognition by Christine Joy Espiritu and Aaron James Singson. In face recognition, many techniques have been proposed. Among them, the most notable is a two-stage PCA+LDA approach Principal Component Analysis (PCA) is used to project images from the original image space into a face-subspace, where dimensionality is reduced and is no longer degenerate, so that LDA can proceed without trouble, PCA (Principal Component Analysis) and LDA (Linear Discriminant Analysis) are methods commonly used for face recognition and verification PCA was used in Human Face Dtection and Recognition by the previous proponents in developing their paper. However, there is a certain research An Efficient LDA Algorithm for Face Recognition by Jie yang, Hua Yu and William Kunz that proves that LDA algorithms outperformed the PCA. On the other hand, there are certain issues that haunt the LDA algorithm.
526			_aF
540			_a5
655			_aacademic writing
942			_alcc _cMS _2lcc
999			_c25424 _d25424