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

fYear

1992

fDate

30 Aug-3 Sep 1992

Firstpage

221

Lastpage

224

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ICPR.1992.201759

Filename

201759