Title :
Face recognition by fractal transformations
Author :
Tan, T. ; Yan, H.
Author_Institution :
Sch. of Electr. & Inf. Eng., Sydney Univ., NSW, Australia
Abstract :
In this paper, we propose a new method for computerized human face recognition using fractal transformations. We show that by utilizing the intrinsic properties of block-wise self-similar transformations in fractal image coding we can use it to perform face recognition. The contractivity factor and the encoding scheme of the fractal encoder are shown to affect recognition rates. Using this method, an average error rate of 1.75% was obtained on the ORL face database
Keywords :
data compression; face recognition; fractals; image coding; transform coding; ORL face database; block-wise self-similar transformations; computerized human face recognition; contractivity factor; error rate; fractal encoder; fractal image coding; fractal transformations; Equations; Face recognition; Fractals; Hidden Markov models; Humans; Image coding; Image databases; Neural networks; Object recognition; Principal component analysis;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1999. Proceedings., 1999 IEEE International Conference on
Conference_Location :
Phoenix, AZ
Print_ISBN :
0-7803-5041-3
DOI :
10.1109/ICASSP.1999.757606
