%P 416-419
%C Penang
%T N-mean kernel filter and normalized correlation for face localization
%A N.N. Dawoud
%A B.B. Samir
%A J. Janier
%D 2011
%R 10.1109/CSPA.2011.5759913
%O cited By 2; Conference of 2011 IEEE 7th International Colloquium on Signal Processing and Its Applications, CSPA 2011 ; Conference Date: 4 March 2011 Through 6 March 2011; Conference Code:84971
%L scholars2086
%J Proceedings - 2011 IEEE 7th International Colloquium on Signal Processing and Its Applications, CSPA 2011
%K Clutter background; Face localization; Face position; Input image; Localization accuracy; Localization errors; Measurement methods; Normalized correlation; Normalized cross-correlation; Pre-processing method; Rectangular block; Similarity measurements; Similarity-matching; Yale University, Face recognition; Signal processing; Template matching, Image matching
%X Recently, Template matching approach has been widely used to locate faces with various pose, illumination and clutter background. Normalized Cross-correlation (NCC) is an effective and simple measurement method to compute the similarity matching between the stored faces templates and the rectangular blocks of the input image to locate the face position. However, localization error occurs very often due to some rectangular blocks which have more face than correct blocks because of the effect of matrices values of these blocks. In this paper we proposed a simple preprocessing method before the use of NCC. This is to reduce the effects of such problems by increasing the values of the input image pixels. The result showed a significant improvement in localization accuracy compared with the use of NCC alone which is only up to 11. Yale University database was used to evaluate our proposed method. © 2011 IEEE.