Title :
Face Recognition Based on Invariant Eigenvectors and Hausdorff Fraction Distance
Author :
Xie, Yonghua ; Setia, Lokesh ; Burkhardt, Hans
Author_Institution :
Inst. of Comput. Sci. & Software, Nanjing Univ. of Inf. Sci. & Technol., Nanjing, China
Abstract :
A method for face recognition based on invariant eigenvectors and Hausdorff Fraction Distance is proposed. With this method, the invariant eigenvectors based on the image edge are firstly extracted. Then by computing the Hausdorff Fraction Distance between the invariant eigenvectors, the process for similarities evaluation is accomplished. Experimental results on the ORL face database validate that the proposed method is invariant to image rotation, minute edge alteration and illumination conditions, and can improve recognition precision and reduce time complexity simultaneously.
Keywords :
edge detection; eigenvalues and eigenfunctions; face recognition; Hausdorff fraction distance; ORL face database; face recognition; image edge extraction; image rotation; invariant eigenvectors; minute edge alteration; similarities evaluation; Computer science; Face recognition; Humans; Image databases; Image recognition; Lighting; Linear discriminant analysis; Principal component analysis; Robustness; Shape;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3735-1
DOI :
10.1109/FSKD.2009.275