recognition system. The method is based on 2D face
image features using subset of non-correlated and
Orthogonal Gabor Filters instead of using the whole
Gabor Filter Bank, then compressing the output feature
vector using Linear Discriminant Analysis (LDA). The
face image has been enhanced using multi stage image
processing technique to normalize it and compensate for
illumination variation. Experimental results show that the
proposed system is effective for both dimension
reduction and good recognition performance when
compared to the complete Gabor filter bank. The system
has been tested using CASIA, ORL and Cropped YaleB
2D face images Databases and achieved average
recognition rate of 98.9 %.