A novel orientation code is proposed for face recognition applications in this paper. Gabor wavelet transform is a
common tool for orientation analysis in a 2D image; whereas Hamming distance is an efficient distance measurement for
multiple classifications such as face identification. Specifically, at each frequency band, an index number representing
the strongest orientational response is selected, and then encoded in binary format to favor the Hamming distance
calculation. Multiple-band orientation codes are then organized into a face pattern byte (FPB) by using order statistics.
With the FPB, Hamming distances are calculated and compared to achieve face identification. The FPB has the
dimensionality of 8 bits per pixel and its performance will be compared to that of FPW (face pattern word, 32 bits per
pixel). The dimensionality of FPB can be further reduced down to 4 bits per pixel, called face pattern nibble (FPN).
Experimental results with visible and thermal face databases show that the proposed orientation code for face
recognition is very promising in contrast with classical methods such as PCA.