Fast face recognition method using high order autocorrelations

24 August 2005

conference paper
Published by Institute of Electrical and Electronics Engineers (IEEE)

Vol. 2, 1297-1300
https://doi.org/10.1109/ijcnn.1993.716783

Abstract

We describe both the implementation and the evaluation of a face recognition method. The feature extraction algorithm is based on the computation of local autocorrelation coefficients. The main characteristics of these coefficients are simplicity of computation and a built-in translational invariance, which allows the system to respond in real time. The classification is realized by conventional methods; namely least square discriminant mapping and linear discriminant analysis, which may be implemented with hardware neural networks. We tested the system on a database of 11600 images of 116 persons. The simulations show peak recognition rates of up to 98% and a satisfactory rejection vs. recognition ratio.

Keywords

This publication has 3 references indexed in Scilit:

A face recognition method using higher order local autocorrelation and multivariate analysis
Published by Institute of Electrical and Electronics Engineers (IEEE) ,2003
Automatic recognition and analysis of human faces and facial expressions: a survey
Pattern Recognition, 1992
Nth-Order autocorrelations in pattern recognition
Information and Control, 1968