Title :
A robust algebraic method for human face recognition
Author :
Cheng, Yong-Qing ; Liu, Ke ; Yang, Jing-Yu ; Wang, Hua-Feng
Author_Institution :
Dept. of Comput. Sci., East China Inst. of Technol., Nanjing, China
fDate :
30 Aug-3 Sep 1992
Abstract :
The feature image and projective image are first proposed to describe the human face, and a new method for human face recognition in which projective images are used for classification is presented. The projective coordinates of projective image on feature images are used as the feature vectors which represent the inherent attributes of human faces. Finally, the feature extraction method of human face images is derived and a hierarchical distance classifier for human face recognition is constructed. The experiments have shown that the recognition method based on the coordinate feature vector is a powerful method for recognizing human face images, and recognition accuracies of 100 percent are obtained for all 64 facial images in eight classes of human faces
Keywords :
face recognition; feature extraction; feature vectors; hierarchical distance classifier; human face recognition; projective image; robust algebraic method; Computer science; Face recognition; Feature extraction; Humans; Image recognition; Mouth; Nose; Pattern recognition; Robustness; Shape;
Conference_Titel :
Pattern Recognition, 1992. Vol.II. Conference B: Pattern Recognition Methodology and Systems, Proceedings., 11th IAPR International Conference on
Conference_Location :
The Hague
Print_ISBN :
0-8186-2915-0
DOI :
10.1109/ICPR.1992.201759