Paper
31 December 2008 Face recognition based on wavelet transform and variance similarity
Dezhong Zheng, Fayi Cui
Author Affiliations +
Proceedings Volume 7130, Fourth International Symposium on Precision Mechanical Measurements; 71303M (2008) https://doi.org/10.1117/12.819689
Event: Fourth International Symposium on Precision Mechanical Measurements, 2008, Anhui, China
Abstract
The image match for face recognition is studied. Variances of sequences in relation to facial images are computed, and the weights used for computation of similarity are obtained by a certain transform between the variance and weight. The weights based on the better theoretical derivation have good stability. And the variance similarity calculated by these weights is of great adaptability, weakening the impact of interferences including the noise and deformation of images. Wavelet transform is a very good method about image compression, by which redundancies of the image are removed and original features of the image are reserved. Whereas pixels of a facial image are usually larger, wavelet transform is used to extract the low-frequency images. And then each facial variance similarity is computed based on the matrix of the low-frequency image. Finally, the image match is carried out for face recognition. The experiments show that the proposed method has the characteristics of simple realization, rapid recognition speed and high recognition rate.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dezhong Zheng and Fayi Cui "Face recognition based on wavelet transform and variance similarity", Proc. SPIE 7130, Fourth International Symposium on Precision Mechanical Measurements, 71303M (31 December 2008); https://doi.org/10.1117/12.819689
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Wavelets

Facial recognition systems

Wavelet transforms

Databases

Image compression

Detection and tracking algorithms

Image processing

Back to Top