DocumentCode :
1594124
Title :
Block DCT Vectors Construction for Face Retrieval Based on Genetic Algorithm
Author :
Xie, Yonghua ; Setia, Lokesh ; Burkhardt, Hans
Author_Institution :
Nanjing Univ. of Inf. Sci. & Technol., Nanjing
Volume :
3
fYear :
2007
Firstpage :
770
Lastpage :
775
Abstract :
Effective feature extraction is one of the most important steps in content-based face image retrieval applications. A vectors construction method for face retrieval based on block DCT and genetic algorithm is proposed in this paper. According to this method, the block DCT coefficients are firstly selected according to the histogram of each block image, and then genetic algorithm is used to select and construct ultimate discriminative vectors for image retrieval. The experimental results on AR gray face database show that the proposed method is robust to facial situations of pose, expression, illumination and partial occlusion, and can get better performance of retrieval accuracy and speed simultaneously.
Keywords :
content-based retrieval; discrete cosine transforms; face recognition; feature extraction; genetic algorithms; image retrieval; block DCT coefficients; content-based face image retrieval; face retrieval; feature extraction; genetic algorithm; image histogram; vectors construction; Content based retrieval; Discrete cosine transforms; Feature extraction; Genetic algorithms; Histograms; Image databases; Image retrieval; Information retrieval; Lighting; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
Type :
conf
DOI :
10.1109/ICNC.2007.286
Filename :
4344613
Link To Document :
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