DocumentCode
2785804
Title
Comparative study of dimension reduction and recognition algorithms of DCT and 2DPCA
Author
Jiang, Bin ; Yang, Guo-Sheng ; Zhang, Huan-long
Author_Institution
Inst. of Adv. Control & Intell. Inf. Process., Henan Univ., Kaifeng
Volume
1
fYear
2008
fDate
12-15 July 2008
Firstpage
407
Lastpage
410
Abstract
Based on the application of DCT (discrete cosine transform) in the image compression, the feasibility of DCT to be used in image feature dimension reduction is analyzed, and the basic principle of the image feature dimension reduction based on DCT is given in this paper. And then, taking the face recognition and the facial expression recognition as the research background, the theoretical analysis that DCT algorithm has the higher recognition than 2DPCA (two-dimensional principal component analysis) in the face recognition and the facial expression recognition is given under the condition that DCT and 2DPCA algorithms have the approximate dimension reduction effect. At last, the comparative simulation experiment is performed on DCT and 2DPCA algorithms respectively by use of the AT&T face database and JAFFE facial expression database.
Keywords
discrete cosine transforms; emotion recognition; face recognition; feature extraction; image coding; principal component analysis; 2DPCA; DCT; JAFFE facial expression database; discrete cosine transform; facial expression recognition; image compression; image feature dimension reduction; two-dimensional principal component analysis; Algorithm design and analysis; Cybernetics; Discrete cosine transforms; Face recognition; Image coding; Image databases; Image recognition; Machine learning; Pattern recognition; Spatial databases; DCT; Facial Expression Recognition; Facial Recognition; Feature Dimension Reduction; Image Compression;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location
Kunming
Print_ISBN
978-1-4244-2095-7
Electronic_ISBN
978-1-4244-2096-4
Type
conf
DOI
10.1109/ICMLC.2008.4620440
Filename
4620440
Link To Document