Disclosed is a human face clustering method merging LBP and Gabor features. The method comprises the steps of: converting three channels, i.e. R, G and B channels of an image into greyscale images so as to obtain an image L; extracting a Gabor feature; extracting an LBP feature; and clustering human faces in a layering mode. The present invention has the positive effects that: by means of performing a human face detection on an image to position a human face region, then conducting LBP and Gabor feature extraction on the positioned human face region, and finally conducting layering clustering on the extracted features, the present invention clusters photographs belonging to the same person together. The feature extraction method of the present invention can effectively restrain the influence of illumination, and effectively restrain the influence of conditions such as posture, hair style and head ornament using the elastic partial matching algorithm when the similarity between human faces is measured. Human faces can be steadily clustered under the interference of complex background, changed illumination, different facial expressions, different human body postures, different hair styles and head ornaments.
HUMAN FACE CLUSTERING METHOD MERGING LBP AND GABOR FEATURES